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市場調查報告書

醫療的認知式運算和人工智能系統

Cognitive Computing and Artificial Intelligence Systems in Healthcare

出版商 Frost & Sullivan 商品編碼 346563
出版日期 內容資訊 英文 69 Pages
商品交期: 最快1-2個工作天內
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醫療的認知式運算和人工智能系統 Cognitive Computing and Artificial Intelligence Systems in Healthcare
出版日期: 2015年12月09日 內容資訊: 英文 69 Pages
簡介

本報告以醫療的人工智能 (AI) 的市場機會為主題,提供市場預測、開發業者的競爭情形相關驗證之系統性資訊。

第1章 摘要整理

第2章 人工智能 (AI) 定義、時間軸、應用

第3章 市場預測

  • 推動因素與阻礙因素
  • 推動市場要素
  • 阻礙市場要素
  • 醫療的AI市場
  • 主要的應用預測

第4章 AI

  • 網際網路,醫療,AI的民主化
  • 醫療提供的存取問題
  • 醫療提供的品質問題
  • 醫療提供的成本問題
  • 決策支援的AI
  • 可應對AI應用的醫療提供的課題
  • 可應對AI應用的患者使用
  • 未來的應用:個別照護的AI
  • 醫療資訊管理上AI應用
  • 腫瘤學的AI案例研究
  • AI的消費者參與
  • 專門的認知系統:整合醫療模式
  • 帶入自己的設備,認知系統模型

第5章 AI系統的產業形勢

  • AI的供應商的生態系統
  • IBM的Watson:醫療平台
  • 主要的夥伴關係:IBM的Watson
  • Cognitive Scale
  • Hindsait
  • AiCure
  • AIme Health Coach
  • 醫療使用的其他專門系統
  • 有前途的參與企業:AI領域的新興企業

第6章 主要結論

第7章 關於Frost&Sullivan

目錄
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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