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ヘルスケアにおける分散学習市場規模、シェア、動向分析レポート：用途別、展開モード別、最終用途別、地域別、セグメント別予測、2025年～2030年

Federated Learning In Healthcare Market Size, Share & Trends Analysis Report By Application, By Deployment Mode (On-premise, Cloud-based), By End-use, By Region, And Segment Forecasts, 2025 - 2030

出版日
ページ情報
英文 200 Pages
納期
2～10営業日
カスタマイズ可能
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=143.74円
ヘルスケアにおける分散学習市場規模、シェア、動向分析レポート：用途別、展開モード別、最終用途別、地域別、セグメント別予測、2025年～2030年
出版日: 2025年04月22日
発行: Grand View Research
ページ情報: 英文 200 Pages
納期: 2～10営業日
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  • 概要
  • 図表
  • 目次
概要

市場規模と動向

世界のヘルスケアにおける分散学習市場規模は、2024年に2,883万米ドルと推定され、2025～2030年にかけて16.0%のCAGRで成長すると予測されています。

分散学習とブロックチェーン技術の統合は、安全かつ協調的なAIモデル開発のための強力なツールとして、ヘルスケアセグメントで大きな注目を集めています。分散学習により、複数のヘルスケア機関は、機密性の高い患者情報を直接共有することなく、そのデータでAIモデルをトレーニングすることができ、プライバシーが確実に維持されます。ブロックチェーン技術は、分散学習システム内のすべてのやり取りを追跡する不変の台帳を提供することで、セキュリティのレイヤーをもう1つ増やします。これにより、データ交換とモデル更新が透明で、監査可能で、改ざん防止されていることが保証され、不正アクセスや不正操作から保護されます。

分散学習とブロックチェーンを組み合わせることで、ヘルスケア機関はAIモデル開発のための分散化された安全なインフラを確立することができます。ブロックチェーンはモデルの更新を検証・追跡し、AIシステムの出力と決定に対する信頼を高めています。この統合により、医療機関間のコラボレーションが促進され、患者の機密を守りつつ、多様なデータセットから洞察を共有することが可能になります。さらに、これらの技術を組み合わせることで、AIシステムのアカウンタビリティが強化され、モデルのトレーニングやデータの取り扱いプロセスの追跡や監査が容易になります。

ヘルスケアでは、分散学習は、複数の機関にまたがるAIモデルをトレーニングするためのユニークな方法を記載しています。このアプローチにより、各機関は機密性の高い患者情報を共有することなく、データを安全かつプライベートに保つことができます。モデルは各機関でローカルに学習され、実際のデータではなくモデルの更新のみが共有されます。このように分散することで、各施設は専門知識とデータの多様性をプールすることができ、ひいてはAIモデルの精度を向上させることができます。最終的に、分散学習は患者の秘密を厳守しながらヘルスケアソリューションを強化する方法を記載しています。例えば、2024年10月、フレッド・ハッチンソンがんセンター、ダナファーバーがんラボ、メモリアル・スローン・ケタリングがんセンター、シドニー・キンメル総合がんセンター、Amazon Web Services、Microsoft、Nvidia、デロイトなどのテック大手との協業により「がんAIアライアンス」が設立され、機密性の高い患者情報を共有することなく、安全で分散化されたデータ分散を可能にする分散学習により、AI主導のがん医療を推進します。

遠隔地では、分散学習により、健康モニタリング用のウェアラブルやスマートフォンなどのエッジデバイスに直接AIモデルを展開することが可能になっています。これらのデバイスは、継続的なインターネットアクセスを必要とせずにローカルデータを処理できるため、接続性の低い環境に理想的です。生データを送信する代わりに、モデルの更新のみが中央サーバーと共有され、データのプライバシーが確保されます。このアプローチにより、心拍数やグルコースレベルなどの健康指標を、デバイス上で直接リアルタイムに分析することが可能になります。統合学習により、ユーザーのプライバシーを損なうことなく、複数のデバイスからのデータでモデルを継続的に改善することができます。これは、慢性疾患の管理や、十分なサービスを受けていない地域での予防ヘルスケアの提供に特に有益です。最終的には、中央集中型のインフラへの依存を減らすと同時に、AIを活用したヘルスケアへのアクセシビリティを高めることができます。

ヘルスケア機関は、患者ケアを強化するためにAI駆動型技術を急速に導入しています。分散学習は、機密データを共有することなく、複数の機関でAIモデルをトレーニングするための安全な方法を記載しています。この分散型アプローチは、コラボレーションを可能にしながら、患者のプライバシーを確実に維持します。データをローカルに維持できるようにすることで、統合学習はセキュリティを維持しながらイノベーションを促進します。また、AIモデルを多様なデータセットで学習させることができるため、さまざまなヘルスケア環境での精度と適用性が向上します。例えば、2024年12月、ドイツのヘルスケア技術企業であるSiemens Healthineersは、NVIDIA Corporationと協業し、MONAI Deployを同社の医療用画像処理プラットフォームに統合しました。この協業は、臨床現場におけるAI主導型ソリューションの展開を加速し、医療機関が医療画像ワークフローに先進的AI技術を導入しやすくすることを目的としています。

目次

第1章 調査手法と範囲

第2章 エグゼクティブサマリー

第3章 ヘルスケアにおける分散学習市場の変数、動向、範囲

  • 世界のヘルスケアにおける分散学習市場の展望
  • 産業バリューチェーン分析
  • 市場力学
    • 市場促進要因分析
    • 市場抑制要因分析
    • 産業の課題
  • ポーターのファイブフォース分析
    • サプライヤーの力
    • 買い手の力
    • 代替の脅威
    • 新規参入からの脅威
    • 競争企業間の敵対関係
  • PESTEL分析
    • 政治
    • 経済
    • 社会
    • 技術
    • 環境
    • 法的

第4章 ヘルスケアにおける分散学習市場：用途の推定と予測

  • ヘルスケアにおける分散学習市場：用途変動分析、2024年と2030年

第5章 ヘルスケアにおける分散学習市場：展開モードの推定と予測

  • ヘルスケアにおける分散学習市場：展開モード変動分析、2024年と2030年

第6章 ヘルスケアにおける分散学習市場：最終用途の展望の推定と予測

  • ヘルスケアにおける分散学習市場：最終用途変動分析、2024年と2030年
    • 病院とヘルスケア機関
    • 製薬とバイオテクノロジー企業
    • 研究機関
    • 政府と規制機関

第7章 ヘルスケアにおける分散学習市場：地域別、推定・動向分析

  • ヘルスケアにおける分散学習市場のシェア（地域別、2024年と2030年、100万米ドル）
  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • 英国
    • ドイツ
    • フランス
  • アジア太平洋
    • 中国
    • 日本
    • インド
    • オーストラリア
    • 韓国
  • ラテンアメリカ
    • ブラジル
  • 中東・アフリカ
    • アラブ首長国連邦
    • サウジアラビア
    • 南アフリカ

第8章 競合情勢

  • 主要市場参入企業による最近の動向と影響分析
  • ベンダー情勢
    • 企業分類
    • 主要販売代理店とチャネルパートナー一覧
    • 潜在顧客一覧
  • 競合力学
    • 競合ベンチマーキング
    • 戦略マッピング
    • ヒートマップ分析
  • 企業プロファイル/上場企業
    • FedML
    • GE Healthcare
    • Google LLC
    • Health Catalyst
    • IBM Corporation
    • Medtronic
    • Microsoft
    • NVIDIA Corporation
    • Owkin, Inc.
    • Siemens Healthineers
図表

List of Tables

  • Table 1 Global Federated Learning in Healthcare market estimates and forecasts, by region, 2018 - 2030 (USD Million)
  • Table 2 Global Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 3 Global Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 4 Global Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 5 North America Federated Learning in Healthcare market estimates and forecasts, by country, 2018 - 2030 (USD Million)
  • Table 6 North America Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 7 North America Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 8 North America Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 9 U.S. Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 10 U.S. Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 11 U.S. Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 12 Canada Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 13 Canada Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 14 Canada Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 15 Mexico Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 16 Mexico Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 17 Mexico Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 18 Europe Federated Learning in Healthcare market estimates and forecasts, by country, 2018 - 2030 (USD Million)
  • Table 19 Europe Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 20 Europe Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 21 Europe Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 22 UK Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 23 UK Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 24 UK Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 25 Germany Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 26 Germany Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 27 Germany Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 28 France Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 29 France Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 30 France Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 31 Asia Pacific Federated Learning in Healthcare market estimates and forecasts, by country, 2018 - 2030 (USD Million)
  • Table 32 Asia Pacific Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 33 Asia Pacific Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 34 Asia Pacific Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 35 China Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 36 China Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 37 China Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 38 Japan Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 39 Japan Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 40 Japan Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 41 India Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 42 India Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 43 India Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 44 Australia Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 45 Australia Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 46 Australia Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 47 South Korea Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 48 South Korea Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 49 South Korea Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 50 Latin America Federated Learning in Healthcare market estimates and forecasts, by country, 2018 - 2030 (USD Million)
  • Table 51 Latin America Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 52 Latin America Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 53 Latin America Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 54 Brazil Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 55 Brazil Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 56 Brazil Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 57 Middle East & Africa Federated Learning in Healthcare market estimates and forecasts, by country, 2018 - 2030 (USD Million)
  • Table 58 Middle East & Africa Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 59 Middle East & Africa Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 60 Middle East & Africa Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 61 Saudi Arabia Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 62 Saudi Arabia Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 63 Saudi Arabia Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 64 UAE Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 65 UAE Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 66 UAE Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)
  • Table 67 South Africa Federated Learning in Healthcare market estimates and forecasts, by Application, 2018 - 2030 (USD Million)
  • Table 68 South Africa Federated Learning in Healthcare market estimates and forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
  • Table 69 South Africa Federated Learning in Healthcare market estimates and forecasts, by End Use, 2018 - 2030 (USD Million)

List of Figures

  • Fig. 1 Federated Learning in Healthcare market segmentation
  • Fig. 2 Market research process
  • Fig. 3 Information procurement
  • Fig. 4 Primary research pattern
  • Fig. 5 Market research approaches
  • Fig. 6 Parent market analysis
  • Fig. 7 Market formulation & validation
  • Fig. 8 Federated Learning in Healthcare market snapshot
  • Fig. 9 Federated Learning in Healthcare market segment snapshot
  • Fig. 10 Federated Learning in Healthcare market competitive landscape snapshot
  • Fig. 11 Market driver relevance analysis (Current & future impact)
  • Fig. 12 Market restraint relevance analysis (Current & future impact)
  • Fig. 13 Value Chain Analysis
  • Fig. 14 Federated Learning in Healthcare market: Application outlook key takeaways (USD Million)
  • Fig. 15 Federated Learning in Healthcare market: Application movement analysis (USD Million), 2024 & 2030
  • Fig. 16 Medical Imaging market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 17 Drug Discovery and Development market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 18 Electronic Health Records (EHR) Analysis market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 19 Remote Patient Monitoring market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 20 Clinical Trials market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 21 Federated Learning in Healthcare market, Deployment Mode outlook key takeaways (USD Million)
  • Fig. 22 Federated Learning in Healthcare market Deployment Mode movement analysis (USD Million), 2024 & 2030
  • Fig. 23 On-Premise market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 24 Cloud-Based market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 25 Federated Learning in Healthcare market: End Use outlook key takeaways (USD Million)
  • Fig. 26 Federated Learning in Healthcare market: End Use movement analysis (USD Million), 2024 & 2030
  • Fig. 27 Hospitals and Healthcare Providers market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 28 Pharmaceutical and Biotechnology Companies market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 29 Research Institutions market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 30 Government and Regulatory Bodies market revenue estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 31 Federated Learning in Healthcare market: Regional outlook, 2024 & 2030, USD Million
  • Fig. 32 North America Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 33 U.S. Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 34 Canada Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 35 Mexico Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 36 Europe Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 37 UK Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 38 Germany Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 39 France Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 40 Asia Pacific Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 41 China Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 42 Japan Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 43 India Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 44 Australia Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 45 South Korea Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 46 Latin America Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 47 Brazil Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 48 MEA Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 49 KSA Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 50 UAE Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 51 South Africa Federated Learning in Healthcare market estimates and forecasts, 2018 - 2030 (USD Million)
  • Fig. 52 Strategy framework
  • Fig. 53 Company Categorization
目次
Product Code: GVR-4-68040-557-3

Market Size & Trends:

The global federated learning in healthcare market size was estimated at USD 28.83 million in 2024 and is projected to grow at a CAGR of 16.0% from 2025 to 2030. The integration of federated learning with blockchain technology is gaining significant prominence in the healthcare sector as a powerful tool for secure and collaborative AI model development. Federated learning allows multiple healthcare institutions to train AI models on their data without directly sharing sensitive patient information, ensuring privacy is maintained. Blockchain technology adds another layer of security by providing an immutable ledger that tracks all interactions within the federated learning system. This ensures that data exchanges and model updates are transparent, auditable, and tamper-proof, which protects against unauthorized access or manipulation.

Combining federated learning with blockchain allows healthcare institutions to establish a decentralized and secure infrastructure for AI model development. Blockchain verifies and tracks model updates, increasing trust in the AI systems' outputs and decisions. This integration promotes greater collaboration across institutions, enabling the sharing of insights from diverse datasets while safeguarding patient confidentiality. Moreover, the combination of these technologies enhances the accountability of AI systems, making it easier to trace and audit model training and data handling processes.

In healthcare, federated learning offers a unique method for training AI models across multiple institutions. This approach enables each institution to keep its data secure and private without sharing sensitive patient information. The model is trained locally at each institution, and only model updates are shared, not the actual data. Collaborating in this way allows institutions to pool their expertise and data diversity, which in turn improves the accuracy of AI models. Ultimately, federated learning provides a way to enhance healthcare solutions while maintaining strict patient confidentiality. For instance, in October 2024, The Cancer AI Alliance is formed through collaboration between Fred Hutchinson Cancer Center, Dana-Farber Cancer Institute, Memorial Sloan Kettering Cancer Center, Sidney Kimmel Comprehensive Cancer Center, and tech giants such as Amazon Web Services, Inc., Microsoft Corporation, NVIDIA Corporation, and Deloitte to advance AI-driven cancer care, to advance AI-driven cancer care through federated learning, which allows secure, decentralized data collaboration without sharing sensitive patient information.

In remote areas, federated learning is enabling the deployment of AI models directly on edge devices such as wearables and smartphones for health monitoring. These devices can process local data without requiring continuous internet access, making them ideal for low-connectivity environments. Instead of sending raw data, only model updates are shared with central servers, ensuring data privacy. This approach allows for real-time analysis of health metrics, such as heart rate or glucose levels, directly on the device. Federated learning allows models to continually improve with data from multiple devices without compromising user privacy. This is particularly beneficial for managing chronic conditions or providing preventative healthcare in underserved regions. Ultimately, it reduces the reliance on centralized infrastructure while enhancing the accessibility of AI-powered healthcare.

Healthcare institutions are rapidly adopting AI-driven technologies to enhance patient care. Federated learning offers a secure method for training AI models across multiple institutions without sharing sensitive data. This decentralized approach ensures that patient privacy is maintained while enabling collaboration. Allowing data to remain local, federated learning fosters innovation while maintaining security. It also enables AI models to be trained on diverse datasets, improving their accuracy and applicability across various healthcare settings. For instance, in December 2024, Siemens Healthineers, a healthcare technology company in Germany, collaborated with NVIDIA Corporation to integrate MONAI Deploy into their medical imaging platforms. This collaboration aims to accelerate the deployment of AI-driven solutions in clinical settings, making it easier for healthcare institutions to implement advanced AI technologies in medical imaging workflows.

Global Federated Learning In Healthcare Market Report Segmentation

This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the latest industry trends and opportunities in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the global federated learning in healthcare market report based on application, deployment mode, end-use, and region:

  • Application Outlook (Revenue, USD Million, 2018 - 2030)
  • Medical Imaging
  • Drug Discovery and Development
  • Electronic Health Records (EHR) Analysis
  • Remote Patient Monitoring
  • Clinical Trials
  • Deployment Mode Outlook (Revenue, USD Million, 2018 - 2030)
  • On-premise
  • Cloud-based
  • End-use Outlook (Revenue, USD Million, 2018 - 2030)
  • Hospitals and Healthcare Providers
  • Pharmaceutical and Biotechnology Companies
  • Research Institutions
  • Government and Regulatory Bodies
  • Regional Outlook (Revenue, USD Million, 2018 - 2030)
  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • UK
    • Germany
    • France
  • Asia Pacific
    • China
    • Japan
    • India
    • Australia
    • South Korea
  • Latin America
    • Brazil
  • Middle East & Africa (MEA)
    • KSA
    • UAE
    • South Africa

Table of Contents

Chapter 1. Methodology and Scope

  • 1.1. Market Segmentation & Scope
  • 1.2. Market Definition
  • 1.3. Information Procurement
    • 1.3.1. Purchased Database
    • 1.3.2. GVR's Internal Database
    • 1.3.3. Secondary Sources & Third-Party Perspectives
    • 1.3.4. Primary Research
  • 1.4. Information Analysis
    • 1.4.1. Data Analysis Models
  • 1.5. Market Formulation & Data Visualization
  • 1.6. Data Validation & Publishing

Chapter 2. Executive Summary

  • 2.1. Market Insights
  • 2.2. Segmental Outlook
  • 2.3. Competitive Outlook

Chapter 3. Federated Learning in Healthcare Market Variables, Trends & Scope

  • 3.1. Global Federated Learning in Healthcare Market Outlook
  • 3.2. Industry Value Chain Analysis
  • 3.3. Market Dynamics
    • 3.3.1. Market Driver Analysis
    • 3.3.2. Market Restraint Analysis
    • 3.3.3. Industry Challenges
  • 3.4. Porter's Five Forces Analysis
    • 3.4.1. Supplier Power
    • 3.4.2. Buyer Power
    • 3.4.3. Substitution Threat
    • 3.4.4. Threat from New Entrant
    • 3.4.5. Competitive Rivalry
  • 3.5. PESTEL Analysis
    • 3.5.1. Political Landscape
    • 3.5.2. Economic Landscape
    • 3.5.3. Social Landscape
    • 3.5.4. Technological Landscape
    • 3.5.5. Environmental Landscape
    • 3.5.6. Legal Landscape

Chapter 4. Federated Learning in Healthcare Market: Application Estimates & Forecasts

  • 4.1. Federated Learning in Healthcare Market: Application Movement Analysis, 2024 & 2030
    • 4.1.1. Medical Imaging
      • 4.1.1.1. Medical Imaging Market estimates and forecast, 2018 - 2030 (USD Million)
    • 4.1.2. Drug Discovery and Development
      • 4.1.2.1. Drug Discovery and Development Market estimates and forecast, 2018 - 2030 (USD Million)
    • 4.1.3. Electronic Health Records (EHR) Analysis
      • 4.1.3.1. Electronic Health Records (EHR) Analysis Market estimates and forecast, 2018 - 2030 (USD Million)
    • 4.1.4. Remote Patient Monitoring
      • 4.1.4.1. Remote Patient Monitoring Market estimates and forecast, 2018 - 2030 (USD Million)
    • 4.1.5. Clinical Trials
      • 4.1.5.1. Clinical Trials Analysis Market estimates and forecast, 2018 - 2030 (USD Million)

Chapter 5. Federated Learning in Healthcare Market: Deployment Mode Estimates & Forecasts

  • 5.1. Federated Learning in Healthcare Market: Deployment Mode Movement Analysis, 2024 & 2030
    • 5.1.1. On-Premise
      • 5.1.1.1. On-Premise Market estimates and forecast, 2018 - 2030 (USD Million)
    • 5.1.2. Cloud-Based
      • 5.1.2.1. Cloud-Based Market estimates and forecast, 2018 - 2030 (USD Million)

Chapter 6. Federated Learning in Healthcare Market: End Use Outlook Estimates & Forecasts

  • 6.1. Federated Learning in Healthcare Market: End Use Movement Analysis, 2024 & 2030
    • 6.1.1. Hospitals and Healthcare Providers
      • 6.1.1.1. Hospitals and Healthcare Providers Market estimates and forecast, 2018 - 2030 (USD Million)
    • 6.1.2. Pharmaceutical and Biotechnology Companies
      • 6.1.2.1. Pharmaceutical and Biotechnology Companies Market estimates and forecast, 2018 - 2030 (USD Million)
    • 6.1.3. Research Institutions
      • 6.1.3.1. Research Institutions Market estimates and forecast, 2018 - 2030 (USD Million)
    • 6.1.4. Government and Regulatory Bodies
      • 6.1.4.1. Government and Regulatory Bodies Market estimates and forecast, 2018 - 2030 (USD Million)

Chapter 7. Federated Learning in Healthcare Market: Regional Estimates & Trend Analysis

  • 7.1. Federated Learning in Healthcare Market Share, By Region, 2024 & 2030, USD Million
  • 7.2. North America
    • 7.2.1. North America Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.2.1.1. North America Federated Learning in Healthcare Market Estimates and Forecasts, by Country, 2018 - 2030 (USD Million)
      • 7.2.1.2. North America Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.2.1.3. North America Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.2.1.4. North America Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.2.2. U.S.
      • 7.2.2.1. U.S. Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.2.2.2. U.S. Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.2.2.3. U.S. Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.2.2.4. U.S. Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.2.3. Canada
      • 7.2.3.1. Canada Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.2.3.2. Canada Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.2.3.3. Canada Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.2.3.4. Canada Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.2.4. Mexico
      • 7.2.4.1. Mexico Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.2.4.2. Mexico Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.2.4.3. Mexico Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.2.4.4. Mexico Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
  • 7.3. Europe
    • 7.3.1. Europe Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.3.1.1. Europe Federated Learning in Healthcare Market Estimates and Forecasts, by Country, 2018 - 2030 (USD Million)
      • 7.3.1.2. Europe Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.3.1.3. Europe Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.3.1.4. Europe Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.3.2. UK
      • 7.3.2.1. UK Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.3.2.2. UK Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.3.2.3. UK Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.3.2.4. UK Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.3.3. Germany
      • 7.3.3.1. Germany Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.3.3.2. Germany Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.3.3.3. Germany Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.3.3.4. Germany Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.3.4. France
      • 7.3.4.1. France Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.3.4.2. France Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.3.4.3. France Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.3.4.4. France Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
  • 7.4. Asia Pacific
    • 7.4.1. Asia Pacific Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.4.1.1. Asia Pacific Federated Learning in Healthcare Market Estimates and Forecasts, by Country, 2018 - 2030 (USD Million)
      • 7.4.1.2. Asia Pacific Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.4.1.3. Asia Pacific Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.4.1.4. Asia Pacific Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.4.2. China
      • 7.4.2.1. China Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.4.2.2. China Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.4.2.3. China Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.4.2.4. China Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.4.3. Japan
      • 7.4.3.1. Japan Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.4.3.2. Japan Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.4.3.3. Japan Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.4.3.4. Japan Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.4.4. India
      • 7.4.4.1. India Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.4.4.2. India Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.4.4.3. India Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.4.4.4. India Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.4.5. Australia
      • 7.4.5.1. Australia Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.4.5.2. Australia Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.4.5.3. Australia Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.4.5.4. Australia Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.4.6. South Korea
      • 7.4.6.1. South Korea Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.4.6.2. South Korea Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.4.6.3. South Korea Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.4.6.4. South Korea Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
  • 7.5. Latin America
    • 7.5.1. Latin America Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.5.1.1. Latin America Federated Learning in Healthcare Market Estimates and Forecasts, by Country, 2018 - 2030 (USD Million)
      • 7.5.1.2. Latin America Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.5.1.3. Latin America Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.5.1.4. Latin America Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.5.2. Brazil
      • 7.5.2.1. Brazil Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.5.2.2. Brazil Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.5.2.3. Brazil Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.5.2.4. Brazil Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
  • 7.6. Middle East and Africa
    • 7.6.1. Middle East and Africa Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.6.1.1. Middle East and Africa Federated Learning in Healthcare Market Estimates and Forecasts, by Country, 2018 - 2030 (USD Million)
      • 7.6.1.2. Middle East and Africa Federated Learning in Healthcare Market Estimates and Forecasts, by Application , 2018 - 2030 (USD Million)
      • 7.6.1.3. Middle East and Africa Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.6.1.4. Middle East and Africa Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.6.2. UAE
      • 7.6.2.1. UAE Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.6.2.2. UAE Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.6.2.3. UAE Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.6.2.4. UAE Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.6.3. KSA
      • 7.6.3.1. KSA Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.6.3.2. KSA Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.6.3.3. KSA Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.6.3.4. KSA Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
    • 7.6.4. South Africa
      • 7.6.4.1. South Africa Federated Learning in Healthcare Market Estimates and Forecasts, 2018 - 2030 (USD Million)
      • 7.6.4.2. South Africa Federated Learning in Healthcare Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
      • 7.6.4.3. South Africa Federated Learning in Healthcare Market Estimates and Forecasts, by Deployment Mode, 2018 - 2030 (USD Million)
      • 7.6.4.4. South Africa Federated Learning in Healthcare Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)

Chapter 8. Competitive Landscape

  • 8.1. Recent Developments & Impact Analysis, By Key Market Participants
  • 8.2. Vendor Landscape
    • 8.2.1. Company categorization
    • 8.2.2. List of Key Distributors and channel Partners
    • 8.2.3. List of Potential Customers/Listing
  • 8.3. Competitive Dynamics
    • 8.3.1. Competitive Benchmarking
    • 8.3.2. Strategy Mapping
    • 8.3.3. Heat Map Analysis
  • 8.4. Company Profiles/Listing
    • 8.4.1. FedML
      • 8.4.1.1. Participant's overview
      • 8.4.1.2. Financial performance
      • 8.4.1.3. Deployment Mode benchmarking
      • 8.4.1.4. Strategic initiatives
    • 8.4.2. GE Healthcare
      • 8.4.2.1. Participant's overview
      • 8.4.2.2. Financial performance
      • 8.4.2.3. Deployment Mode benchmarking
      • 8.4.2.4. Strategic initiatives
    • 8.4.3. Google LLC
      • 8.4.3.1. Participant's overview
      • 8.4.3.2. Financial performance
      • 8.4.3.3. Deployment Mode benchmarking
      • 8.4.3.4. Strategic initiatives
    • 8.4.4. Health Catalyst
      • 8.4.4.1. Participant's overview
      • 8.4.4.2. Financial performance
      • 8.4.4.3. Deployment Mode benchmarking
      • 8.4.4.4. Strategic initiatives
    • 8.4.5. IBM Corporation
      • 8.4.5.1. Participant's overview
      • 8.4.5.2. Financial performance
      • 8.4.5.3. Deployment Mode benchmarking
      • 8.4.5.4. Strategic initiatives
    • 8.4.6. Medtronic
      • 8.4.6.1. Participant's overview
      • 8.4.6.2. Financial performance
      • 8.4.6.3. Deployment Mode benchmarking
      • 8.4.6.4. Strategic initiatives
    • 8.4.7. Microsoft
      • 8.4.7.1. Participant's overview
      • 8.4.7.2. Financial performance
      • 8.4.7.3. Deployment Mode benchmarking
      • 8.4.7.4. Strategic initiatives
    • 8.4.8. NVIDIA Corporation
      • 8.4.8.1. Participant's overview
      • 8.4.8.2. Financial performance
      • 8.4.8.3. Deployment Mode benchmarking
      • 8.4.8.4. Strategic initiatives
    • 8.4.9. Owkin, Inc.
      • 8.4.9.1. Participant's overview
      • 8.4.9.2. Financial performance
      • 8.4.9.3. Deployment Mode benchmarking
      • 8.4.9.4. Strategic initiatives
    • 8.4.10. Siemens Healthineers
      • 8.4.10.1. Participant's overview
      • 8.4.10.2. Financial performance
      • 8.4.10.3. Deployment Mode benchmarking
      • 8.4.10.4. Strategic initiatives