医療における人工知能市場：コンポーネント、技術タイプ、展開モード、応用分野、エンドユーザー、疾患タイプ別-2025-2030年の世界予測

医療における人工知能市場は、2024年には126億4,000万米ドルとなり、2025年には156億2,000万米ドル、CAGR24.37%で成長し、2030年には468億1,000万米ドルに達すると予測されています。

人工知能は、比類ない精度とスピードで病気を診断、治療、管理する革新的な手法を導入することで、現代医療の状況を急速に変えつつあります。医療専門家や意思決定者は現在、複雑な医療データを分析するだけでなく、患者の転帰向上に役立つ実用的な洞察を提供する強力なアルゴリズムや高度なコンピューティングシステムを活用しています。本レポートでは、ヘルスケアにおけるAIの多面的な進化を詳細に調査し、その導入の背後にある主な促進要因と、業界を前進させる変革的なシフトを強調しています。

ヘルスケアのニーズと画期的な技術アプリケーションの融合により、臨床とオペレーションの両方の効率が大幅に改善される環境が整いつつあります。各利害関係者がデジタルトランスフォーメーションの採用に向けて動き出す中、従来の慣行と将来を見据えた技術革新とのギャップを埋めることが重視されるようになっています。このダイナミックなエコシステムにおいて、AIの統合は孤立した現象ではなく、ヘルスケアのバリューチェーンのあらゆるレベルに関わるシステム的な変化です。

本レポートは、包括的な調査と厳密な分析を通じて、主要な動向、セグメンテーションの洞察、地域差、これらの変化を先導する主要企業にスポットを当てることで、業界関係者にとって貴重なリソースとなることを目指しています。この分野が成熟し続ける中、利害関係者は、競争力を維持し、AI主導のヘルスケアイノベーションの可能性を最大限に活用するために、これらの複雑な相互作用に関する微妙な理解を深める必要があります。

医療におけるAIの情勢を形成する変革的シフト

ヘルスケア業界は、人工知能の普及に牽引され、大きな変革期を迎えています。かつては未来的な概念と見なされていたものが、今や日常的なヘルスケアの重要な要素となり、診断から治療に至るまであらゆる側面を再構築しています。研究、投資、政策の見直しにより、AI技術が医療イノベーションの最前線に位置づけられるようになり、業界の情勢は変化しています。

特筆すべきは、この変革がサービス指向とソフトウェア主導の両方の要素を包含していることです。一方では、構成要素に関して市場を詳細に調査すると、サービスとソフトウェアという2つの焦点があることがわかる。サービスのうち、コンサルティングと統合・展開サービスは、ヘルスケア機関のダイナミックなニーズによりよく適応するよう最適化されています。一方、ソフトウェアは極めて重要な役割を担っており、アプリケーション・ソフトウェアとシステム・ソフトウェアが、複雑な分析と意思決定プロセスに必要な技術的バックボーンを提供しています。

コンポーネントの細分化に加え、技術進化も変革の重要な原動力となっています。コンピュータビジョン、機械学習、自然言語処理、ロボット工学などの技術は、医療データの解釈方法を再定義するだけでなく、リアルタイムの意思決定や個別化医療を促進します。この総合的なアプローチは、クラウドベースとオンプレミスの両方のソリューションを含む戦略的な導入形態によってさらに補完され、ヘルスケア組織が堅牢なデータセキュリティと高いパフォーマンスを維持しながらインフラコストを最適化できることを保証しています。

医療におけるAIの応用分野は、診断、創薬、治療手法などへと拡大しています。診断領域そのものは、医用画像や病理学的検出の技術革新によって進歩を遂げ、より正確で早期な病気の発見を可能にしています。これと並行して、創薬や治療介入への取り組みも、研究や臨床試験を効率化するAI搭載技術によって加速しています。

この進化は、病院、診療所、製薬会社、研究機関などのエンドユーザー部門に対する洗練された理解にも及んでいます。これらの各グループは、テーラーメイドのAIアプリケーションから利益を得ており、技術の展開が効果的であるだけでなく、ユーザーのニーズに特に合致していることを保証しています。さらに、循環器科、皮膚科、消化器科、神経科、産婦人科、腫瘍科、眼科、整形外科、小児科、泌尿器科などの疾患タイプを詳細に調査することで、市場戦略がさらに洗練されています。こうしたカテゴリーに基づく洞察により、利害関係者は特定の分野を成長と経営強化のターゲットとすることができます。

全体として、医療分野におけるAIに見られる変革的なシフトは、従来のパラダイムの強固な再構成を示唆しています。テクノロジーによって強化されたヘルスケアが単なる可能性ではなく、より正確で効率的な患者中心のケアを提供する標準となる未来を垣間見ることができます。

市場セグメンテーションの詳細な洞察

市場セグメンテーションを包括的に理解することは、AIのヘルスケアへの統合の多面的な性質を把握するために不可欠です。セグメンテーションの枠組みは、内在的領域と運用的領域を区別することで、市場分析のバックボーンを形成します。最初のセグメンテーションは、コンポーネントに基づいて、サービスとソフトウェアに分析的に深堀りします。サービス面ではさらに、AI技術のシームレスな導入を保証するコンサルタント主導の戦略と統合プラス展開ソリューションに分岐します。一方、ソフトウェア・セグメントは、エンドユーザー・インターフェイスに対応するアプリケーション・ソフトウェアと、重要なバックエンド機能を処理するシステム・ソフトウェアに分類して綿密に調査します。

2つ目のセグメンテーション層では、テクノロジーの種類に焦点を当て、コンピューター・ビジョン、機械学習、自然言語処理、ロボット工学のレンズを通して市場を分析します。各技術は、複雑な診断画像の解釈から、膨大なデータセットに基づく正確な治療計画の策定まで、医療処置の特定のセグメントを変革する可能性について評価されます。この総合的なアプローチにより、市場参入企業は、技術的能力とヘルスケアのニーズを合致させるオポチュニティのポケットを特定することができます。

導入形態を検討することで、さらにきめ細かな分析が可能になります。オンプレミス・ソリューションに対するクラウドベースの評価では、スケーラビリティ、セキュリティ、費用対効果を考慮した分析を行うことで、組織の運用フレームワークに最適な選択肢を提供します。

セグメンテーション分析はアプリケーション分野にも及び、診断、創薬、治療といった異なるグループが精査されています。診断分野では、臨床上の意思決定の重要な原動力として登場した医用画像や病理学的検出などのサブセグメントに顕著な焦点が当てられていることは興味深いです。

同様に重要なのはエンドユーザーに関する詳細な調査であり、これにはヘルスケアプロバイダー、製薬会社、学術センターと並ぶ研究機関を含む多様なセットが含まれます。ヘルスケアプロバイダーの中では、診療所と病院の両方が特に注目されており、異なる臨床現場におけるAIの導入規模や範囲が多様であることを反映しています。

最後のセグメンテーションでは、循環器科から皮膚科、消化器科、神経科、産婦人科、腫瘍科、眼科、整形外科、小児科、泌尿器科に至るまで、疾患の種類を考察しています。この分類により、技術的介入から最も恩恵を受けると思われる臨床分野を網羅的に把握することができ、利害関係者は実際の疾病の流行や治療の進歩に合わせて調査や投資戦略を立てることができます。

これらのセグメンテーションの洞察を総合すると、市場は一枚岩ではなく、各コンポーネント、技術、展開モード、応用分野、エンドユーザー、疾患タイプが相互に作用して、医療におけるAIの現在と将来の可能性を包括的に理解する複雑なタペストリーであることが明らかになります。このセグメンテーションの深さと広さは、的を絞った戦略とタイムリーな介入のためのロードマップを提供し、業界リーダーがヘルスケア情勢の当面のニーズと長期的動向の両方を反映した意思決定を行うことを可能にします。

目次

第1章 序文

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 市場の概要

第5章 市場洞察

• 市場力学
  • 促進要因
    • 世界の人口高齢化により、高齢者のケアと管理を支援するAIソリューションの需要が高まっています。
    • 個別化医療の需要増加がヘルスケアにおけるAI技術の成長を促進
  • 抑制要因
    • 医療分野におけるAI技術の初期導入コストの高さとROIへの懸念
  • 機会
    • 医療分野におけるAIの開発と導入に向けたテクノロジー企業とヘルスケア提供者間の提携の増加
    • ロボット手術にAIを統合することで、精度の向上、回復時間の短縮、手術リスクの最小化を実現
  • 課題
    • ヘルスケアにおける人工知能の訓練を受けた熟練専門家の不足
• 市場セグメンテーション分析
  • テクノロジーの種類：データに基づく洞察を通じて患者ケアの成果を向上させるための医療における機械学習テクノロジーの導入
  • エンドユーザー：病院における診断画像や予測分析のための人工知能の利用
• ポーターのファイブフォース分析
• PESTEL分析
  • 政治的
  • 経済
  • 社会
  • 技術的
  • 法律上
  • 環境

第6章 医療における人工知能市場：コンポーネント別

• サービス
  • コンサルティングサービス
  • 統合および導入サービス
• ソフトウェア
  • アプリケーションソフトウェア
  • システムソフトウェア

第7章 医療における人工知能市場テクノロジーの種類別

• コンピュータービジョン
• 機械学習
• 自然言語処理
• ロボット工学

第8章 医療における人工知能市場：展開モード別

• クラウドベース
• オンプレミス

第9章 医療における人工知能市場アプリケーション分野別

• 診断
  • 医療画像
  • 病理検出
• 創薬
• 治療

第10章 医療における人工知能市場：エンドユーザー別

• ヘルスケア提供者
  • クリニック
  • 病院
• 製薬会社
• 調査機関および学術センター

第11章 医療における人工知能市場：疾患タイプ別

• 心臓病学
• 皮膚科
• 消化器内科
• 神経学
• 産婦人科
• 腫瘍学
• 眼科
• 整形外科
• 小児科
• 泌尿器科

第12章 南北アメリカの医療における人工知能市場

• アルゼンチン
• ブラジル
• カナダ
• メキシコ
• 米国

第13章 アジア太平洋地域の医療における人工知能市場

• オーストラリア
• 中国
• インド
• インドネシア
• 日本
• マレーシア
• フィリピン
• シンガポール
• 韓国
• 台湾
• タイ
• ベトナム

第14章 欧州・中東・アフリカの医療における人工知能市場

• デンマーク
• エジプト
• フィンランド
• フランス
• ドイツ
• イスラエル
• イタリア
• オランダ
• ナイジェリア
• ノルウェー
• ポーランド
• カタール
• ロシア
• サウジアラビア
• 南アフリカ
• スペイン
• スウェーデン
• スイス
• トルコ
• アラブ首長国連邦
• 英国

第15章 競合情勢

• 市場シェア分析, 2024
• FPNVポジショニングマトリックス, 2024
• 競合シナリオ分析
• 戦略分析と提言

企業一覧

• Aidoc Medical Ltd.
• Allscripts Healthcare Solutions, Inc.
• BenevolentAI Limited
• Butterfly Network, Inc.
• CloudMedx Inc.
• Enlitic, Inc.
• Epic Systems Corporation
• Exscientia plc
• Freenome Holdings, Inc.
• GE Healthcare
• Google LLC By Alphabet Inc.
• HeartFlow, Inc.
• IBM Corporation
• Insilico Medicine, Inc.
• Intel Corporation
• Koninklijke Philips N.V.
• Medtronic plc
• NVIDIA Corporation
• Owkin, Inc.
• PathAI, Inc.
• Qventus, Inc.
• Recursion Pharmaceuticals, Inc.
• Siemens Healthineers AG
• Tempus Labs, Inc.
• Viz.ai, Inc.
• Zebra Medical Vision Ltd.

LIST OF FIGURES

• FIGURE 1. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET MULTI-CURRENCY
• FIGURE 2. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET MULTI-LANGUAGE
• FIGURE 3. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET RESEARCH PROCESS
• FIGURE 4. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, 2024 VS 2030
• FIGURE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, 2018-2030 (USD MILLION)
• FIGURE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY REGION, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2024 VS 2030 (%)
• FIGURE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2024 VS 2030 (%)
• FIGURE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2030 (%)
• FIGURE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2024 VS 2030 (%)
• FIGURE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2024 VS 2030 (%)
• FIGURE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2024 VS 2030 (%)
• FIGURE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 20. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
• FIGURE 21. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 22. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY STATE, 2024 VS 2030 (%)
• FIGURE 23. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY STATE, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 24. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
• FIGURE 25. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 26. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
• FIGURE 27. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
• FIGURE 28. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SHARE, BY KEY PLAYER, 2024
• FIGURE 29. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET, FPNV POSITIONING MATRIX, 2024

LIST OF TABLES

• TABLE 1. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SEGMENTATION & COVERAGE
• TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
• TABLE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, 2018-2030 (USD MILLION)
• TABLE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY REGION, 2018-2030 (USD MILLION)
• TABLE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
• TABLE 6. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET DYNAMICS
• TABLE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, BY REGION, 2018-2030 (USD MILLION)
• TABLE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY CONSULTING SERVICES, BY REGION, 2018-2030 (USD MILLION)
• TABLE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY INTEGRATION & DEPLOYMENT SERVICES, BY REGION, 2018-2030 (USD MILLION)
• TABLE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
• TABLE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATIONS SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
• TABLE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SYSTEM SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
• TABLE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPUTER VISION, BY REGION, 2018-2030 (USD MILLION)
• TABLE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2018-2030 (USD MILLION)
• TABLE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY REGION, 2018-2030 (USD MILLION)
• TABLE 20. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY ROBOTICS, BY REGION, 2018-2030 (USD MILLION)
• TABLE 21. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 22. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY CLOUD-BASED, BY REGION, 2018-2030 (USD MILLION)
• TABLE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY ON-PREMISE, BY REGION, 2018-2030 (USD MILLION)
• TABLE 24. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 25. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, BY REGION, 2018-2030 (USD MILLION)
• TABLE 26. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY MEDICAL IMAGING, BY REGION, 2018-2030 (USD MILLION)
• TABLE 27. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY PATHOLOGY DETECTION, BY REGION, 2018-2030 (USD MILLION)
• TABLE 28. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 29. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DRUG DISCOVERY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TREATMENT, BY REGION, 2018-2030 (USD MILLION)
• TABLE 31. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 32. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, BY REGION, 2018-2030 (USD MILLION)
• TABLE 33. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY CLINICS, BY REGION, 2018-2030 (USD MILLION)
• TABLE 34. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HOSPITALS, BY REGION, 2018-2030 (USD MILLION)
• TABLE 35. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 36. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY PHARMACEUTICAL COMPANIES, BY REGION, 2018-2030 (USD MILLION)
• TABLE 37. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY RESEARCH INSTITUTES & ACADEMIC CENTERS, BY REGION, 2018-2030 (USD MILLION)
• TABLE 38. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 39. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY CARDIOLOGY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 40. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DERMATOLOGY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 41. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY GASTROENTEROLOGY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 42. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY NEUROLOGY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 43. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY OBSTETRICS & GYNECOLOGY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 44. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY ONCOLOGY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 45. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY OPHTHALMOLOGY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 46. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY ORTHOPEDICS, BY REGION, 2018-2030 (USD MILLION)
• TABLE 47. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY PEDIATRICS, BY REGION, 2018-2030 (USD MILLION)
• TABLE 48. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY UROLOGY, BY REGION, 2018-2030 (USD MILLION)
• TABLE 49. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 50. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 51. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 52. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 53. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 54. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 55. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 56. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 57. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 58. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 59. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
• TABLE 60. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 61. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 62. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 63. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 64. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 65. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 66. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 67. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 68. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 69. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 70. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 71. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 72. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 73. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 74. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 75. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 76. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 77. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 78. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 79. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 80. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 81. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 82. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 83. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 84. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 85. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 86. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 87. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 88. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 89. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 90. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 91. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 92. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 93. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 94. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 95. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 96. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 97. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 98. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 99. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 100. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 101. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 102. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 103. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 104. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 105. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 106. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 107. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 108. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 109. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 110. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
• TABLE 111. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 112. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 113. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 114. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 115. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 116. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 117. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 118. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 119. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 120. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 121. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
• TABLE 122. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 123. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 124. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 125. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 126. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 127. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 128. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 129. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 130. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 131. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 132. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 133. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 134. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 135. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 136. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 137. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 138. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 139. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 140. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 141. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 142. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 143. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 144. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 145. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 146. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 147. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 148. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 149. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 150. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 151. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 152. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 153. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 154. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 155. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 156. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 157. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 158. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 159. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 160. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 161. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 162. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 163. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 164. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 165. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 166. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 167. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 168. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 169. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 170. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 171. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 172. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 173. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 174. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 175. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 176. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 177. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 178. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 179. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 180. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 181. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 182. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 183. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 184. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 185. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 186. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 187. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 188. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 189. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 190. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 191. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 192. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 193. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 194. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 195. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 196. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 197. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 198. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 199. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 200. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 201. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 202. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 203. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 204. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 205. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 206. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 207. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 208. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 209. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 210. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 211. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 212. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 213. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 214. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 215. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 216. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 217. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 218. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 219. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 220. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 221. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 222. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 223. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 224. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 225. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 226. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 227. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 228. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 229. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 230. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 231. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 232. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 233. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 234. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 235. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 236. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 237. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 238. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 239. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 240. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 241. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 242. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 243. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 244. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 245. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 246. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 247. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 248. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 249. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 250. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 251. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 252. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
• TABLE 253. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 254. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 255. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 256. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 257. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 258. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 259. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 260. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 261. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 262. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 263. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 264. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 265. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 266. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 267. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 268. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 269. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 270. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 271. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 272. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 273. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 274. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 275. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 276. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 277. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 278. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 279. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 280. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 281. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 282. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 283. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 284. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 285. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 286. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
• TABLE 287. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
• TABLE 288. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
• TABLE 289. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
• TABLE 290. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
• TABLE 291. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
• TABLE 292. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
• TABLE 293. GERMANY ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
• TABLE 294. GERMANY ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
• TABLE 295. GERMANY ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
• TABLE 296. GERMANY ART

The Artificial Intelligence in Medicine Market was valued at USD 12.64 billion in 2024 and is projected to grow to USD 15.62 billion in 2025, with a CAGR of 24.37%, reaching USD 46.81 billion by 2030.

Artificial Intelligence is rapidly transforming the landscape of modern medicine by introducing innovative methods to diagnose, treat, and manage diseases with unparalleled precision and speed. Medical professionals and decision-makers are now leveraging powerful algorithms and advanced computing systems that not only analyze complex medical data but also provide actionable insights which help in enhancing patient outcomes. This report provides an in-depth look into the multi-faceted evolution of AI in healthcare, underscoring the major drivers behind its adoption and the transformative shifts propelling the industry forward.

The convergence of healthcare needs with breakthrough technological applications is creating an environment where both clinical and operational efficiencies can be significantly improved. As each stakeholder moves towards embracing digital transformation, there is a growing emphasis on bridging gaps between traditional practices and future-forward technological innovations. In this dynamic ecosystem, the integration of AI is not an isolated phenomenon but a systemic change that touches on all levels of the healthcare value chain.

Through comprehensive research and rigorous analysis, this report aims to serve as a valuable resource for industry professionals by highlighting key trends, segmentation insights, regional variations, and the leading companies spearheading these changes. As the field continues to mature, stakeholders must develop a nuanced understanding of these complex interactions to stay competitive and harness the full potential of AI-driven healthcare innovations.

Transformative Shifts Reshaping the AI in Medicine Landscape

The healthcare industry is undergoing a seismic transformation driven by the pervasive adoption of Artificial Intelligence. What was once seen as a futuristic concept is now a crucial component of everyday healthcare, reshaping every facet from diagnostics to treatment. The industry landscape has shifted as research, investment, and policy revisions place AI technologies at the forefront of medical innovation.

Notably, the transformation encompasses both service-oriented and software-driven elements. On one hand, a detailed study of the market with respect to components reveals a dual focus: services and software. Within services, consulting and integration & deployment services are being optimized to better adapt to the dynamic needs of healthcare institutions. On the other hand, software plays a pivotal role, with applications software and system software providing the technical backbone required for complex analyses and decision-making processes.

In addition to component segmentation, technological evolution underlines a critical driver of transformation. Technologies such as computer vision, machine learning, natural language processing, and robotics are not only redefining how medical data is interpreted but are also facilitating real-time decision-making and personalized care. This holistic approach is further complemented by strategic deployment modes that include both cloud-based and on-premise solutions, ensuring that healthcare organizations can optimize infrastructure costs while maintaining robust data security and high performance.

Application areas of AI in medicine have expanded to include diagnostics, drug discovery, and treatment methodologies. The diagnostic domain itself has seen advancements through medical imaging and pathology detection innovations, thereby enabling more accurate and early detection of diseases. In parallel, efforts in drug discovery and therapeutic interventions are being accelerated by AI-powered techniques that streamline research and clinical trials.

This evolution extends to a refined understanding of end-user sectors such as hospitals, clinics, pharmaceutical companies, and research institutes. Each of these groups benefits from tailored AI applications, ensuring that the deployment of technology is not only effective but also specifically aligned with user needs. Moreover, a detailed exploration of disease types including cardiology, dermatology, gastroenterology, neurology, obstetrics & gynecology, oncology, ophthalmology, orthopedics, pediatrics, and urology has further refined market strategies. These category-based insights enable stakeholders to target specific areas for growth and operational enhancement.

Overall, the transformative shifts observed in AI within the medical realm signal a robust reconfiguration of traditional paradigms. They offer a glimpse into a future where technology-enhanced healthcare isn't just a possibility but a standard, offering more precise, efficient, and patient-centric care.

In-Depth Insight into Market Segmentation

A comprehensive understanding of market segmentation is essential to grasp the multifaceted nature of AI's integration into healthcare. The segmentation framework forms the backbone of market analysis by differentiating between the intrinsic and operational domains. The first segmentation, based on component, takes an analytical deep dive into services and software. The services aspect further branches into consultancy-led strategies and integration plus deployment solutions that ensure seamless adoption of AI technology. Whereas the software segment is meticulously examined by categorizing it into applications software that caters to end-user interfaces and system software which handles critical back-end functions.

The second segmentation layer focuses on technology type, dissecting the market through the lenses of computer vision, machine learning, natural language processing, and robotics. Each technology is evaluated on its potential to transform specific segments of medical procedures, from interpreting complex diagnostic images to formulating precise treatment plans based on vast datasets. This holistic approach enables market participants to identify pockets of opportunity that align technological capabilities with healthcare needs.

Further granularity is achieved by examining the deployment mode. In evaluating cloud-based against on-premise solutions, the analysis takes into account scalability, security, and cost-effectiveness, thereby equipping organizations with the choices that best suit their operational framework.

The segmentation analysis extends into application areas where distinct groups such as diagnostics, drug discovery, and treatment are scrutinized. It is interesting to note that within the diagnostic sphere, there is a pronounced focus on sub-segments like medical imaging and pathology detection, which have emerged as key drivers of clinical decision-making.

Equally important is the detailed study of end-users, which includes a diverse set encompassing healthcare providers, pharmaceutical companies, and research institutes alongside academic centers. Among healthcare providers, both clinics and hospitals are given specific attention, reflecting the varied scale and scope of AI implementation across different clinical settings.

The final segmentation dimension considers disease types, offering insights across a spectrum that ranges from cardiology through dermatology, gastroenterology, neurology, obstetrics & gynecology, oncology, ophthalmology, orthopedics, pediatrics, and urology. This categorization provides an exhaustive view of the clinical areas that stand to benefit most from technological interventions, allowing stakeholders to align research and investment strategies with actual disease prevalence and treatment advancements.

In synthesizing these segmentation insights, it becomes evident that the market is not monolithic but rather a complex tapestry where each component, technology, deployment mode, application area, end-user, and disease type interplays to form a comprehensive understanding of AI's current and future potential in medicine. The depth and breadth of this segmentation offer a roadmap for targeted strategies and timely interventions, allowing industry leaders to make decisions that reflect both immediate needs and long-term trends in the healthcare landscape.

Based on Component, market is studied across Services and Software. The Services is further studied across Consulting Services and Integration & Deployment Services. The Software is further studied across Applications Software and System Software.

Based on Technology Type, market is studied across Computer Vision, Machine Learning, Natural Language Processing, and Robotics.

Based on Deployment Mode, market is studied across Cloud-Based and On-Premise.

Based on Application Areas, market is studied across Diagnostics, Drug Discovery, and Treatment. The Diagnostics is further studied across Medical Imaging and Pathology Detection.

Based on End-User, market is studied across Healthcare Providers, Pharmaceutical Companies, and Research Institutes & Academic Centers. The Healthcare Providers is further studied across Clinics and Hospitals.

Based on Disease Type, market is studied across Cardiology, Dermatology, Gastroenterology, Neurology, Obstetrics & Gynecology, Oncology, Ophthalmology, Orthopedics, Pediatrics, and Urology.

Key Regional Insights Driving Global Trends

Regional trends play a critical role in shaping the overall market dynamics for AI in medicine. Different regions display varied levels of adoption, technological infrastructure, and regulatory environments, each contributing uniquely to the market's evolution. In the Americas, there is a high concentration of healthcare innovation driven by robust funding ecosystems, advanced research facilities, and early technology adoption. This region's ecosystem supports rapid integration of AI-driven solutions into clinical workflows and operational strategies, leading to improvements in patient outcomes and cost efficiencies.

Across Europe, the Middle East, and Africa, regulatory frameworks and public-private partnerships serve as catalysts for technological growth. Investments in technology, bolstered by localized research initiatives, have fostered an environment conducive to both incremental improvements in existing systems and breakthrough innovations. This area emphasizes balanced growth where stringent regulatory measures ensure patient safety while promoting industry-wide advancements in AI applications.

In the Asia-Pacific region, rapid digital transformation is fueled by increasing healthcare demands and a growing population whose needs drive innovative solutions. The region benefits from supportive government policies that encourage technology transfer and collaborative research. These strategies have led to significant advancements in personalized medicine, efficient healthcare delivery, and the overall expansion of AI's footprint in various segments of the healthcare market.

The diverse regional nuances reflect how different factors such as policy frameworks, economic dynamics, and cultural considerations shape market strategies. Stakeholders who understand these regional insights can better navigate the complexities of international markets while tailoring their approaches to maximize local advantages. By leveraging regional strengths and addressing unique challenges, industry leaders are positioned to capitalize on growth opportunities and steer the evolution of AI in medicine on a global scale.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

Comprehensive Analysis of Leading Industry Players

The competitive landscape of AI in medicine is marked by a broad spectrum of companies that are spearheading innovation and market transformation. Various renowned organizations are actively shaping the future of healthcare through breakthrough research, strategic partnerships, and a relentless focus on delivering value. Notable players include Aidoc Medical Ltd., Allscripts Healthcare Solutions, Inc., and BenevolentAI Limited, each contributing robust expertise in technology integration and clinical application. Additional influential companies such as Butterfly Network, Inc. and CloudMedx Inc. are driving advancements in diagnostics and real-time analytics while Enlitic, Inc. and Epic Systems Corporation continue to refine their offerings, ensuring that complex medical data translates into actionable insights.

Further stirring the industry are companies like Exscientia plc and Freenome Holdings, Inc., which have made significant inroads in drug discovery and cancer diagnostics respectively. Solid examples of this trend include GE Healthcare and Google LLC by Alphabet Inc., both harnessing vast swathes of data to optimize medical imaging and operational efficiency. HeartFlow, Inc. and IBM Corporation have also been pivotal in integrating AI technologies into routine clinical analyses, ensuring that the healthcare ecosystem becomes more predictive and responsive.

Other key contributors include Insilico Medicine, Inc., Intel Corporation, and Koninklijke Philips N.V., which are recognized for their innovative approaches to healthcare challenges. Medtronic plc and NVIDIA Corporation are advancing the frontier of medical device innovation with AI-powered capabilities, while companies such as Owkin, Inc. and PathAI, Inc. stand out for their cutting-edge research in pathology and diagnostics. Qventus, Inc. alongside Recursion Pharmaceuticals, Inc. are redefining operational efficiencies and drug formulation techniques, further complemented by the advancements of Siemens Healthineers AG and Tempus Labs, Inc.

Prominent players such as Viz.ai, Inc. and Zebra Medical Vision Ltd. illustrate a continued drive toward making AI accessible in everyday clinical practice. The diverse portfolios and proven track records of these companies underscore not only the technological advances within the medical field but also the importance of strategic positioning and continuous innovation. Their collective efforts are instrumental in bridging the gap between emerging research trends and real-world application, ensuring that AI continues to elevate standards of care across the globe.

The report delves into recent significant developments in the Artificial Intelligence in Medicine Market, highlighting leading vendors and their innovative profiles. These include Aidoc Medical Ltd., Allscripts Healthcare Solutions, Inc., BenevolentAI Limited, Butterfly Network, Inc., CloudMedx Inc., Enlitic, Inc., Epic Systems Corporation, Exscientia plc, Freenome Holdings, Inc., GE Healthcare, Google LLC By Alphabet Inc., HeartFlow, Inc., IBM Corporation, Insilico Medicine, Inc., Intel Corporation, Koninklijke Philips N.V., Medtronic plc, NVIDIA Corporation, Owkin, Inc., PathAI, Inc., Qventus, Inc., Recursion Pharmaceuticals, Inc., Siemens Healthineers AG, Tempus Labs, Inc., Viz.ai, Inc., and Zebra Medical Vision Ltd.. Actionable Recommendations for Industry Leaders

In light of the evolving landscape and multifaceted segmentation detailed above, industry leaders are advised to take several specific steps to secure a competitive advantage and drive sustainable growth. An immediate priority should be the strategic adoption of flexible technology solutions that seamlessly bridge cloud-based and on-premise infrastructures, ensuring both scalability and security. Leaders must explore integrating advanced analytical tools that harness the power of machine learning, computer vision, natural language processing, and robotics. This integrative approach can streamline complex operations and improve clinical outcomes without a steep learning curve or disruptive process changes.

Moreover, it is crucial to align market entry strategies with a strong understanding of regional differences. Companies operating across the Americas, Europe, the Middle East, Africa, and Asia-Pacific should tailor their tactics to address specific regulatory frameworks, healthcare funding models, and patient demographics unique to each region. Establishing localized research initiatives and forging robust collaborations with local healthcare providers and academic institutions can also catalyze innovation and facilitate the easier adoption of AI-driven processes.

Investment in specialized segmentation such as consulting, integration, and advanced system software should be prioritized to maximize operational efficiencies. Industry players would benefit from developing dedicated teams focused on monitoring emerging trends in diagnostics, drug discovery, and treatment, ensuring that strategies remain aligned with the latest scientific and technological breakthroughs.

Concurrently, fostering partnerships with leading technology vendors and research institutions will enable an agile response to rapidly evolving market dynamics. It is advisable to allocate resources toward continuous training programs and workshops to ensure that teams are well-versed in leveraging state-of-the-art AI applications effectively.

Adopting these recommendations, while maintaining a keen focus on both immediate and long-term objectives, will empower industry leaders to not only anticipate future market shifts but also act decisively in harnessing the unprecedented potential of AI to transform healthcare delivery.

Conclusion: Embracing a Future Driven by AI Innovation

In summary, the penetration of Artificial Intelligence into the realm of medicine signifies a paradigm shift that transcends traditional clinical methodologies. Every segment of the market-from service and software components to advanced technology types and nuanced deployment models-demonstrates that AI is not simply an add-on but a crucial catalyst for a complete reengineering of healthcare delivery. Detailed segmentation insights reveal a multi-dimensional space, where innovations in diagnostics, drug discovery, and therapeutic solutions are tailored to meet diverse needs. Furthermore, regional variations and the strategic positioning of leading companies collectively offer a roadmap for sustainable market growth.

Ultimately, the confluence of these trends, dynamics, and actionable recommendations paints a clear picture of a future where technology and medicine converge to offer transformative results. As stakeholders continue to invest in and integrate AI, the trajectory of medical innovation will be characterized by improved patient care, reduced operational friction, and a new era of data-driven clinical excellence. By embracing these shifts, the medical community is poised to lead the charge towards an ecosystem that is both efficient and adaptive to the ever-changing landscape of healthcare.

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Market Dynamics
  • 5.1.1. Drivers
    • 5.1.1.1. Global aging demographics are creating a demand for AI solutions to support elderly care and management
    • 5.1.1.2. Increased demand for personalized medicine fuels the growth of AI technologies in healthcare
  • 5.1.2. Restraints
    • 5.1.2.1. High initial implementation costs and ROI concerns for AI technologies in medicine
  • 5.1.3. Opportunities
    • 5.1.3.1. Rising partnerships between technology companies and healthcare providers for developent and adoption of AI in medicine
    • 5.1.3.2. Integration of AI in robotic surgery to enhance precision, reduce recovery times, and minimize surgical risks
  • 5.1.4. Challenges
    • 5.1.4.1. Shortage of skilled professionals trained in artificial intelligence for healthcare
• 5.2. Market Segmentation Analysis
  • 5.2.1. Technology Type: Adoption of machine leaning technology in medicine for improving patient care outcomes through data-driven insights
  • 5.2.2. End-User: Usage of artificial inteligence in hospitals for diagnostic imaging, and predictive analytics
• 5.3. Porter's Five Forces Analysis
  • 5.3.1. Threat of New Entrants
  • 5.3.2. Threat of Substitutes
  • 5.3.3. Bargaining Power of Customers
  • 5.3.4. Bargaining Power of Suppliers
  • 5.3.5. Industry Rivalry
• 5.4. PESTLE Analysis
  • 5.4.1. Political
  • 5.4.2. Economic
  • 5.4.3. Social
  • 5.4.4. Technological
  • 5.4.5. Legal
  • 5.4.6. Environmental

6. Artificial Intelligence in Medicine Market, by Component

• 6.1. Introduction
• 6.2. Services
  • 6.2.1. Consulting Services
  • 6.2.2. Integration & Deployment Services
• 6.3. Software
  • 6.3.1. Applications Software
  • 6.3.2. System Software

7. Artificial Intelligence in Medicine Market, by Technology Type

• 7.1. Introduction
• 7.2. Computer Vision
• 7.3. Machine Learning
• 7.4. Natural Language Processing
• 7.5. Robotics

8. Artificial Intelligence in Medicine Market, by Deployment Mode

• 8.1. Introduction
• 8.2. Cloud-Based
• 8.3. On-Premise

9. Artificial Intelligence in Medicine Market, by Application Areas

• 9.1. Introduction
• 9.2. Diagnostics
  • 9.2.1. Medical Imaging
  • 9.2.2. Pathology Detection
• 9.3. Drug Discovery
• 9.4. Treatment

10. Artificial Intelligence in Medicine Market, by End-User

• 10.1. Introduction
• 10.2. Healthcare Providers
  • 10.2.1. Clinics
  • 10.2.2. Hospitals
• 10.3. Pharmaceutical Companies
• 10.4. Research Institutes & Academic Centers

11. Artificial Intelligence in Medicine Market, by Disease Type

• 11.1. Introduction
• 11.2. Cardiology
• 11.3. Dermatology
• 11.4. Gastroenterology
• 11.5. Neurology
• 11.6. Obstetrics & Gynecology
• 11.7. Oncology
• 11.8. Ophthalmology
• 11.9. Orthopedics
• 11.10. Pediatrics
• 11.11. Urology

12. Americas Artificial Intelligence in Medicine Market

• 12.1. Introduction
• 12.2. Argentina
• 12.3. Brazil
• 12.4. Canada
• 12.5. Mexico
• 12.6. United States

13. Asia-Pacific Artificial Intelligence in Medicine Market

• 13.1. Introduction
• 13.2. Australia
• 13.3. China
• 13.4. India
• 13.5. Indonesia
• 13.6. Japan
• 13.7. Malaysia
• 13.8. Philippines
• 13.9. Singapore
• 13.10. South Korea
• 13.11. Taiwan
• 13.12. Thailand
• 13.13. Vietnam

14. Europe, Middle East & Africa Artificial Intelligence in Medicine Market

• 14.1. Introduction
• 14.2. Denmark
• 14.3. Egypt
• 14.4. Finland
• 14.5. France
• 14.6. Germany
• 14.7. Israel
• 14.8. Italy
• 14.9. Netherlands
• 14.10. Nigeria
• 14.11. Norway
• 14.12. Poland
• 14.13. Qatar
• 14.14. Russia
• 14.15. Saudi Arabia
• 14.16. South Africa
• 14.17. Spain
• 14.18. Sweden
• 14.19. Switzerland
• 14.20. Turkey
• 14.21. United Arab Emirates
• 14.22. United Kingdom

15. Competitive Landscape

• 15.1. Market Share Analysis, 2024
• 15.2. FPNV Positioning Matrix, 2024
• 15.3. Competitive Scenario Analysis
  • 15.3.1. GE HealthCare unveils AI innovation lab to revolutionize medical technology
  • 15.3.2. Stryker's strategic acquisition of care.ai to enhance AI-driven healthcare solutions
  • 15.3.3. GE HealthCare strengthens ultrasound capabilities with AI acquisition
• 15.4. Strategy Analysis & Recommendation

Companies Mentioned

• 1. Aidoc Medical Ltd.
• 2. Allscripts Healthcare Solutions, Inc.
• 3. BenevolentAI Limited
• 4. Butterfly Network, Inc.
• 5. CloudMedx Inc.
• 6. Enlitic, Inc.
• 7. Epic Systems Corporation
• 8. Exscientia plc
• 9. Freenome Holdings, Inc.
• 10. GE Healthcare
• 11. Google LLC By Alphabet Inc.
• 12. HeartFlow, Inc.
• 13. IBM Corporation
• 14. Insilico Medicine, Inc.
• 15. Intel Corporation
• 16. Koninklijke Philips N.V.
• 17. Medtronic plc
• 18. NVIDIA Corporation
• 19. Owkin, Inc.
• 20. PathAI, Inc.
• 21. Qventus, Inc.
• 22. Recursion Pharmaceuticals, Inc.
• 23. Siemens Healthineers AG
• 24. Tempus Labs, Inc.
• 25. Viz.ai, Inc.
• 26. Zebra Medical Vision Ltd.