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市場調查報告書

人工智能 (AI) - 全球醫療保健的應用的前10名:2018-2022年

Artificial Intelligence-Top 10 Applications in Healthcare, Global, 2018-2022

出版商 Frost & Sullivan 商品編碼 841539
出版日期 內容資訊 英文 71 Pages
商品交期: 最快1-2個工作天內
價格
人工智能 (AI) - 全球醫療保健的應用的前10名:2018-2022年 Artificial Intelligence-Top 10 Applications in Healthcare, Global, 2018-2022
出版日期: 2019年04月26日內容資訊: 英文 71 Pages
簡介

本報告提供醫療保健市場上人工智能 (AI) 應用的相關調查,未來的產業需求,投資趨勢,從市場適應性,及進化的供應商的生態系統等分析,10個主要應用領域識別,成長機會,CTA (推薦行動) 、重要的成功要素,課題,及策略必要事項等彙整資料。

摘要整理

簡介 - 醫療保健資料生態系統及AI所扮演的角色

  • 醫療保健的資料的發展
  • 醫療保健資料來源、經濟
  • 醫療保健資料生態系統的AI、分析所扮演的角色
  • 主要趨勢:主要市場影響要素的影響

成長機會的評估 - 醫療保健市場上AI應用

  • 醫療保健的AI - 引進的時間軸
  • 主要相關利益者的醫療保健AI的機會
  • 醫療保健的AI應用 - 潛在成本節約的機會
  • 醫療保健AI的機會評估組成架構
  • 醫療保健AI的應用領域
  • 醫療保健AI的資金分析:各主要的利用案例
  • 醫療保健AI的資金分析:各地區
  • AI產品分析:各疾病的分類、應用領域

CTA (推薦行動) : 醫療保健的AI應用的前10名

  • 醫療保健的AI應用的前10名:主要供應商的生態系統
  • 藥物研發、研究 - CTA
  • 醫療圖像、診斷 - CTA
  • 臨床決策支援系統 - CTA
  • 預測分析與風險分析 - CTA
  • 生活方式管理、監測 - CTA
  • 穿戴式/感測器資料分析 - CTA
  • 慢性疾病管理 - CTA
  • 虛擬助手 - CTA
  • 心理健康 - CTA
  • 重症加護室、手術 - CTA

結論、策略必要事項

附錄

Frost & Sullivan

目錄
Product Code: 9AB9/AD

Exploring Key Investment Trends, Companies-to-Action, and Growth Opportunities for AI in the Healthcare Industry

Artificial intelligence (AI) is exhibiting real promise across multiple industries. The healthcare industry is leading the charge when it comes to focused AI application development and attracting AI investment globally. With improvements in healthcare data acquisition and computing power, AI is becoming more of a reality each day. Frost & Sullivan projects that AI and machine learning (ML) will further evolve human and machine interaction across several so far known and probably not well-known applications in healthcare. In the short term (the next 12 to 18 months), the priority will be to bring AI/cognitive platform technology use cases closer to clinical care to augment physicians and even patients with actionable decision-making ability. In particular, AI will begin to see fruition in the imaging diagnostic and drug discovery applications. In the next 2-3 years, AI will become a common theme across all digital initiatives and platforms. Moving forward, as clinicians start to embrace early AI applications, the healthcare industry will start to recognize the limitations of AI and explore the balance between machine-human intelligence. However, pricing for AI solutions remains a critical issue as end-users are often not convinced enough to dedicate an additional budgets for such IT capabilities. A cost-effective approach with clear evidence for potential return on investment (ROI) for both parties can help sustain market growth.

Research Scope:

As part of the Growth Opportunities (GO) research process, Frost & Sullivan analysts review the emerging application of AI across focused healthcare application areas by analyzing future industry needs, investment trends, market readiness, and the evolving vendor ecosystem in the healthcare AI space. The main purpose of this study is to analyze and call out major growth opportunities for AI applications in the healthcare industry. Frost & Sullivan performed a qualitative factor analysis by evaluating critical attributes to identify and assess the top 10 AI applications in the healthcare space. This study provides a high-level market overview and investment trends for identified AI applications in the healthcare industry. It, however, does not provide any forecasts for the AI application market for healthcare.

This study analyzes over 250 global companies which are active in providing AI solutions for healthcare applications. Additionally, it provides an assessment of the emerging AI vendor ecosystem and also a capability profile for select Companies to Action across the identified top 10 application areas of AI in the healthcare industry. Amongst these, we identified market disruptors, including both start-ups and established enterprises, which have the potential to shape future application growth. Finally, the study summarizes key success factors and strategic imperatives for healthcare stakeholders.

Key Issues Addressed:

  • What are the Top 10 areas in healthcare which are ripe for innovation and which could change healthcare using AI and data?
  • What are the unique companies that are introducing innovative AI solutions for focused healthcare applications? What are the select Companies-to-Action by major AI application areas?
  • What are the immediate lucrative growth opportunities and future cost savings potential for AI applications across major healthcare stakeholders?
  • What are the global and regional funding trends for major AI applications in healthcare?
  • What are the critical success factors, challenges, and strategic imperatives for considering AI applications in the healthcare space?
  • How will the future vendor ecosystem for AI applications in the healthcare industry look like?

Table of Contents

1. ARTIFICIAL INTELLIGENCE-TOP 10 APPLICATIONS IN HEALTHCARE, GLOBAL, 2018-2022

Executive Summary

  • Key Findings
  • Study Scope and Segmentation
  • Key Questions this Study will Answer
  • Healthcare AI Opportunity Assessment Framework
  • Healthcare AI Funding Analysis: 2012-2018
  • Top 5 Growth Opportunities-AI in Healthcare
  • Value Chain Analysis by Major Stakeholder and Application Focus
  • Strategic Imperatives for AI Application in Healthcare

Introduction-Healthcare Data Ecosystem and Role of AI

  • Evolution of Data in Healthcare
  • Healthcare Data Sources and Economy
  • Role of AI and Analytics in Healthcare Data Ecosystems
  • Key Trends-Impact of Major Market Influencers

Growth Opportunity Assessment-AI Application in Healthcare Market

  • AI in Healthcare-Timeline for Adoption
  • Healthcare AI Opportunities across Major Stakeholders
  • AI Application in Healthcare-Potential Cost-Saving Opportunities
  • Healthcare AI Opportunity Assessment Framework
  • Healthcare AI Application Areas
  • Healthcare AI Application Areas (continued)
  • Healthcare AI Application Areas (continued)
  • Healthcare AI Funding Analysis (2012-2018)-By Major Use Cases
  • Healthcare AI Funding Analysis (2012-2018)-By Geographic Region
  • AI Product Breakdown by Disease Categories and Application Areas

Companies-to-Action by Top 10 AI Applications in Healthcare

  • Top 10 AI Applications in Healthcare-Select Vendor Ecosystem
  • Drug Discovery and Research-Companies to Watch
  • Medical Imaging and Diagnostics-Companies to Watch
  • Clinical Decision Support System-Companies to Watch
  • Clinical Decision Support System-Companies to Watch (continued)
  • Predictive Insight and Risk Analytics-Companies to Watch
  • Lifestyle Management and Monitoring-Companies to Watch
  • Lifestyle Management and Monitoring-Companies to Watch (continued)
  • Wearables/Sensor Data Insight-Companies to Watch
  • Wearables/Sensor Data Insight-Companies to Watch (continued)
  • Chronic Condition Management-Companies to Watch
  • Chronic Condition Management-Companies to Watch (continued)
  • Virtual Assistance-Companies to Watch
  • Virtual Assistance-Companies to Watch (continued)
  • Mental Health-Companies to Watch
  • Mental Health-Companies to Watch (continued)
  • Emergency Room and Surgery-Companies to Watch
  • Emergency Room and Surgery-Companies to Watch (continued)

Conclusion and Strategic Imperatives

  • Types of Revenue Generators in AI for Healthcare Applications
  • AI Convergence Potential with Emerging Technologies
  • Critical Challenges and Imperatives for Healthcare AI Initiatives
  • Key Conclusions-Five Industry Needs Critical for Future Strategies
  • 3 Big Predictions
  • Legal Disclaimer

Appendix

  • Major Global Tech Companies with Healthcare AI Solutions
  • Major Healthcare IT Companies with AI Solutions
  • Other Key New Companies in the AI Space
  • Other Key New Companies in the AI Space (continued)
  • List of Exhibits
  • List of Exhibits (continued)

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