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市場調査レポート

医療におけるコグニティブコンピューティングと人工知能システム

Cognitive Computing and Artificial Intelligence Systems in Healthcare

発行 Frost & Sullivan 商品コード 346563
出版日 ページ情報 英文 69 Pages
納期: 即日から翌営業日
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医療におけるコグニティブコンピューティングと人工知能システム Cognitive Computing and Artificial Intelligence Systems in Healthcare
出版日: 2015年12月09日 ページ情報: 英文 69 Pages
概要

当レポートでは、医療における人工知能 (AI) の市場機会について取り上げ、市場予測を提供するほか、開発業者の競合情勢について検証して、体系的な情報を提供しています。

第1章 エグゼクティブサマリー

第2章 人工知能 (AI) の定義、タイムライン、応用

第3章 市場予測

  • 促進要因と抑制要因
  • 市場促進要因
  • 市場抑制要因
  • 医療におけるAI市場
  • 主な応用予測

第4章 AI

  • インターネット、医療、AIの民主化
  • 医療提供におけるアクセス問題
  • 医療提供における品質問題
  • 医療提供におけるコスト問題
  • 意思決定支援のAI
  • AIアプリケーションで対処可能な医療提供の課題
  • AIアプリケーションで対処可能な患者のアクセス
  • 将来のアプリケーション:個別ケアにおけるAI
  • 医療情報管理におけるAIアプリケーション
  • オンコロジーにおけるAIのケーススタディ
  • AIによる消費者エンゲージメント
  • 専門のコグニティブシステム:統合医療モデル
  • 自分のデバイスを持ち込み、コグニティブシステムモデル

第5章 AIシステムの産業情勢

  • AIにおけるベンダーのエコシステム
  • IBMのWatson:医療プラットフォーム
  • 主なパートナーシップ:IBMのWatson
  • Cognitive Scale
  • Hindsait
  • AiCure
  • AIme Health Coach
  • 医療で使用するその他の専門システム
  • 有望な参入企業:AI分野の新興企業

第6章 主な結論

第7章 Frost & Sullivanについて

目次
Product Code: NFFE-01-00-00-00

Ramping Up a $6 Billion Dollar Market Opportunity

Shifts to how healthcare is delivered, where it is delivered, and how it is paid for are necessitating adoption of innovative tools for managing information. A key challenge is to appropriately assess the importance of various quantitative metrics, as well as correlate with qualitative recommendations and patient history. The voluminous forms of unstructured data generated across a wide number of fragmented systems necessitate artificial intelligence-enabled systems to correlate information, recognize patterns, and generate insights. This study looks at the market opportunity for artificial intelligence in healthcare, provides market forecasts, and assesses the competitive landscape of developers.

Table of Contents

1. EXECUTIVE SUMMARY

Executive Summary

  • 1. Research Scope
  • 2. Key Questions this Study will Answer
  • 3. Themes for Artificial Intelligence Applications in Healthcare
  • 4. Themes for Artificial Intelligence Applications in Healthcare (continued)
  • 5. Themes for Artificial Intelligence Applications in Healthcare (continued)
  • 6. AI in Clinical Applications
  • 7. AI in Workflow Optimization
  • 8. AI for the Consumer
  • 9. CEO's Perspective
  • 10. Market Projection
  • 11. Three Big Predictions

2. ARTIFICIAL INTELLIGENCEDEFINITION, TIMELINE, AND APPLICATIONS

Artificial IntelligenceDefinition, Timeline, and Applications

  • 1. Artificial Intelligence Ecosystem Segmentation
  • 2. Why Artificial Intelligence?
  • 3. Timeline-Evolution of AI Capabilities
  • 4. How AI is Being Used Today
  • 5. How AI is Being Used Today (continued)
  • 6. AI in Healthcare Timeline for Adoption

3. MARKET PROJECTIONS

Market Projections

  • 1. Drivers and Restraints
  • 2. Drivers Explained
  • 3. Restraints Explained
  • 4. Artificial Intelligence in Healthcare Market
  • 5. Artificial Intelligence in Healthcare Market Discussion
  • 6. Key Application Projection

4. ARTIFICIAL INTELLIGENCE

Artificial Intelligence

  • 1. Democratization of Internet, Healthcare, and AI
  • 2. Access Problems in Care Delivery
  • 3. Quality Problems in Care Delivery
  • 4. Cost Problems in Care Delivery
  • 5. Artificial Intelligence for Decision Support
  • 6. Care Delivery Challenges Addressable through AI Applications
  • 7. Patient Access to Care Addressed through AI Applications
  • 8. Future Applications-AI in Individualized Care
  • 9. AI Applications in Health Information Management
  • 10. AI in Oncology Case Study
  • 11. AI in Oncology Case Study (continued)
  • 12. Consumer Engagement through AI
  • 13. Expert Cognitive Systems-Integrated Health Model
  • 14. Expert Cognitive Systems-Integrated Health Model (continued)
  • 15. Bring Your Device Cognitive Systems Model
  • 16. Bring Your Device Cognitive Systems Model (continued)

5. INDUSTRY LANDSCAPE FOR ARTIFICIAL INTELLIGENCE SYSTEMS

Industry Landscape for Artificial Intelligence Systems

  • 1. Ecosystem of Vendors within AI
  • 2. IBM's Watson Health Platform
  • 3. IBM Watson Health-Population Health Management Capabilities and Features
  • 4. Key Partnerships-IBM Watson
  • 5. Key Partnerships-IBM Watson (continued)
  • 6. Key Partnerships-IBM Watson (continued)
  • 7. Cognitive Scale's Insights Fabric Cognitive Platform
  • 8. Hindsait's SaaS-AI Platform
  • 9. AiCure's Advanced Medication Adherence Solutions
  • 10. AIme Health Coach
  • 11. Other Expert Systems Used in Healthcare
  • 12. Promising Participants-Key New Companies in the AI Space

6. KEY CONCLUSIONS

Key Conclusions

  • 1. Strategies for Success in Building an AI-centric Business Model
  • 2. Legal Disclaimer

7. THE FROST & SULLIVAN STORY

The Frost & Sullivan Story

  • 1. The Frost & Sullivan Story
  • 2. Value Proposition: Future of Your Company & Career
  • 3. Global Perspective
  • 4. Industry Convergence
  • 5. 360° Research Perspective
  • 6. Implementation Excellence
  • 7. Our Blue Ocean Strategy
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