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市場調查報告書

醫療用途的人工智能 (AI) 市場分析·預測:醫療圖像分析,醫療保健VDA (虛擬數位助手),電腦輔助藥物設計,治療方法的建議,患者資料處理

Artificial Intelligence for Healthcare Applications - Medical Image Analysis, Healthcare VDAs, Computational Drug Discovery, Medical Treatment Recommendation, Patient Data Processing and Other Use Cases: Market Analysis and Forecasts

出版商 Tractica 商品編碼 557959
出版日期 內容資訊 英文 82 Pages; 85 Tables, Charts & Figures
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醫療用途的人工智能 (AI) 市場分析·預測:醫療圖像分析,醫療保健VDA (虛擬數位助手),電腦輔助藥物設計,治療方法的建議,患者資料處理 Artificial Intelligence for Healthcare Applications - Medical Image Analysis, Healthcare VDAs, Computational Drug Discovery, Medical Treatment Recommendation, Patient Data Processing and Other Use Cases: Market Analysis and Forecasts
出版日期: 2018年08月27日 內容資訊: 英文 82 Pages; 85 Tables, Charts & Figures
簡介

全球醫療用途的人工智能 (AI) 解決方案市場規模,預測將從2017年的10億美元,到2025年擴大到340億美元以上。

本報告提供醫療用途的人工智能 (AI的)市場調查,彙整市場及技術概要,市場成長的促進因素及課題分析,硬體設備·軟體·業務收益的變化與預測,及主要加入企業的簡介等資訊。

第1章 摘要整理

第2章 市場課題

  • 市場成長的促進要素
    • 數位健康革命
    • 成本節約
    • 資料處理的課題、其他
  • 醫療用AI的利用案例
    • 自動生成報告
    • 生物標記發現
    • 叢集·表現型發現、其他
  • 其他未來的利用案例
    • AI機器人支援手術
    • 患者分診·管理
  • 市場障礙·課題
    • 資料隱私的課題·網路安全的疑慮
    • 醫生·供應商的懷疑性看法
    • 技術·生態系統、其他複雜

第3章 技術課題

  • AI定義
  • 監督 vs. 無監督學習系統
  • 監督學習技術
    • 人工神經網
    • 決定架構/決策樹
    • 單純貝氏分類器
  • 無監督學習技術
    • 深層學習/Deep學習
    • 叢集演算法
  • 技術課題
    • 處理能力
    • 再現性
  • 智慧互動
  • 自然語言處理
  • 個性化
  • 人工智能技術市場成長

第4章 主要參與企業

  • 簡介
  • 企業簡介
    • 3Scan
    • Ada
    • AIME, Inc.
    • AntWorks
    • Arterys
    • Babylon Health
    • Bright.md
    • Deontics
    • Enlitic
    • Hexoskin
    • Hindsait
    • IBM Watson
    • iCarbonX
    • Lark
    • Livongo
    • Maxwell MRI
    • Orbita Inc.
    • Pieces Technologies, Inc.
    • Sentrian
    • XOresearch
    • Zebra Medical Vision
    • Zephyr Health

第5章 市場預測

  • 市場預測·區分
  • 全球收益預測
  • 地區區分
    • 軟體收益:各地區
    • 硬體設備收益:各地區
    • 業務收益:各地區
  • 醫療用AI軟體預測
    • 醫療圖像分析
    • 患者VDA (虛擬數位助手)
    • 電腦輔助藥物設計
    • 治療方法的建議
    • 患者資料處理
    • 醫療診斷援助
    • 將文書工作轉換為數位資料
    • 自動產生報告
    • 醫院患者管理系統
    • 生物標記票務
  • 醫療用AI硬體設備預測
  • 業務收益預測
    • 雲端型業務收益
    • 服務收益明細:各服務分類
  • 結論·建議

第6章 企業名錄

第7章 縮寫·簡稱清單

第8章 目錄

第9章 圖表

第10章 調查範圍·資訊來源·調查手法·註記

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目錄
Product Code: AIH-18

Healthcare has undergone a significant transformation over the past several years, moving from an antiquated, paper-based records system to a more efficient and integrated system that often incorporates physician, payer, and patient-generated health data. This explosion of data means there is a strong need and des ire for systems that not only will help extract and organize this information, but will also analyze and even provide insights and recommendations on how best to utilize the data.

It is no secret that healthcare is expensive. Controlling and reducing costs is a major driver of many healthcare initiatives, and incorporating artificial intelligence (AI) technology is no exception. Contrary to consumer markets, there is little desire to deploy new technology for technology's sake; healthcare has many safety and operational issues that prevent the frivolous introduction of technology, which yields little benefit. AI applications generally are designed to address specific, real-world use cases that make the diagnosis, monitoring, and treatment of patients more efficient, accurate, and available to populations around the world. In the context of an industry fueled by these key market drivers, Tractica forecasts that the global market for AI solutions in the healthcare sector will increase from $1 billion in 2017 to more than $34 billion by 2025.

This Tractica report focuses on 22 healthcare-focused use cases for artificial intelligence, including an assessment of the market opportunity for AI software, hardware, and services in the healthcare market. The market analysis and forecasts within the study cover industry dynamics in five major world regions and are based on an in-depth assessment of major companies as well as startup-level activity in the healthcare AI space. Revenue forecasts for each use case are segmented by world region, and the study also includes profiles of 22 key industry players.

Key Questions Addressed:

  • How much revenue will be generated by the sale of AI-based hardware, software, and services focused on the healthcare market?
  • Which use cases are projected to generate the most revenue throughout the forecast period?
  • What types of AI technology will be used in healthcare?
  • Which hospitals and other providers are utilizing AI-based applications and services?
  • What types of future AI use cases may be on the horizon?
  • Which geographic regions are projected to generate the most revenue in healthcare AI?
  • Which vendors have developed AI-based technologies and are currently selling into the market?

Who Needs This Report?

  • Artificial intelligence technology companies
  • Semiconductor and component vendors
  • Service providers and systems integrators
  • Medical device and healthcare software companies
  • Health systems, healthcare insurance companies, provider networks
  • Government agencies
  • Investor community

Table of Contents

SECTION 1 Executive Summary

  • 1.1 Artificial Intelligence on the Rise
  • 1.2 Market Drivers
    • 1.2.1 Digital Healthcare Revolution
    • 1.2.2 Rising Costs
    • 1.2.3 Disease Management
    • 1.2.4 Increasing Utilization of Electronic Health Records
    • 1.2.5 Improvements in Natural Language Processing and Computer Vision
    • 1.2.6 Increasing Complexity
  • 1.3 Market Barriers
    • 1.3.1 Physician and Provider Skepticism
    • 1.3.2 Technology and Ecosystem Complexity
    • 1.3.3 Regulatory Questions
  • 1.4 Market Forecasts

SECTION 2 Market Issues

  • 2.1 Market Drivers
    • 2.1.1 The Digital Health Revolution
    • 2.1.2 Cost Savings
    • 2.1.3 Data Handling Challenges
    • 2.1.4 Active Disease Research, Treatment, and Management
    • 2.1.5 Growth of Genomic Sequencing Databases
    • 2.1.6 Increasing Utilization of Electronic Health Records
    • 2.1.7 Improvements in Natural Language Processing and Computer Vision
    • 2.1.8 Increasing Complexity
  • 2.2 Healthcare AI Use Cases
    • 2.2.1 Automated Report Generation
    • 2.2.2 Biomarker Discovery
    • 2.2.3 Clustering and Phenotype Discovery
    • 2.2.4 Computational Drug Discovery and Drug Effectiveness
    • 2.2.5 Converting Paperwork into Digital Data
    • 2.2.6 Counterfeit Drug Analysis
    • 2.2.7 Digital Pathology
    • 2.2.8 Face Recognition
    • 2.2.9 Genomic Data Mapping and Analysis for Personalized Healthcare and Precision Medicine
    • 2.2.10 Hospital Patient Management System
    • 2.2.11 Market Intelligence for Scientific Research
    • 2.2.12 Medical Diagnosis Assistance
    • 2.2.13 Medical Image Analysis
    • 2.2.14 Medical Treatment Recommendation
    • 2.2.15 Medication Compliance for Clinical Trials and General Usage
    • 2.2.16 Methods for Monitoring Vitals
    • 2.2.17 Mining, Processing, and Making Sense of Clinical Notes
    • 2.2.18 Patient Data Processing
    • 2.2.19 Portable and Low-Cost Ultrasound Device
    • 2.2.20 Predicting Illness and Patient Outcomes
    • 2.2.21 Text Classification and Mining for Biomedical Literature
    • 2.2.22 Healthcare VDAs
  • 2.3 Other Future Use Cases
    • 2.3.1 AI Robot-Assisted Surgery
    • 2.3.2 Patient Triage and Management
  • 2.4 Market Barriers and Challenges
    • 2.4.1 Data Privacy Issues and Cybersecurity Concerns
    • 2.4.2 Physician and Provider Skepticism
    • 2.4.3 Technology and Ecosystem Complexity
    • 2.4.4 Regulatory Questions

SECTION 3 Technology Issues

  • 3.1 Definition of AI
  • 3.2 Supervised versus Unsupervised Learning Systems
  • 3.3 Supervised Learning Technologies
    • 3.3.1 Artificial Neural Networks
    • 3.3.2 Decision Trees
    • 3.3.3 Naïve Bayes Classifiers
  • 3.4 Unsupervised Learning Technologies
    • 3.4.1 Deep Learning
    • 3.4.2 Clustering Algorithms
  • 3.5 Technical Challenges
    • 3.5.1 Processing Power
    • 3.5.2 Repeatability
  • 3.6 Smart Interaction
  • 3.7 Natural Language Processing
  • 3.8 Personalization
  • 3.9 AI Technology Market Growth

SECTION 4 Key Industry Players

  • 4.1 Introduction
  • 4.2 Company Profiles
    • 4.2.1 3Scan
    • 4.2.2 Ada
    • 4.2.3 AIME Inc
    • 4.2.4 AntWorks
    • 4.2.5 Arterys
    • 4.2.6 Babylon Health
    • 4.2.7 Bright.md
    • 4.2.8 Deontics
    • 4.2.9 Enlitic
    • 4.2.10 Hexoskin
    • 4.2.11 Hindsait
    • 4.2.12 IBM Watson
    • 4.2.13 iCarbonX
    • 4.2.14 Lark
    • 4.2.15 Livongo
    • 4.2.16 Maxwell MRI
    • 4.2.17 Orbita Inc.
    • 4.2.18 Pieces Technologies, Inc.
    • 4.2.19 Sentrian
    • 4.2.20 XOresearch
    • 4.2.21 Zebra Medical Vision
    • 4.2.22 Zephyr Health

SECTION 5 Market Forecasts

  • 5.1 Market Forecast and Segmentation
  • 5.2 Global Revenue Forecasts
  • 5.3 Regional Segmentation
    • 5.3.1 Software Revenue by Region
    • 5.3.2 Hardware Revenue by Region
    • 5.3.3 Services Revenue by Region
  • 5.4 Healthcare AI Software Forecasts
    • 5.4.1 Medical Image Analysis
    • 5.4.2 Healthcare VDAs
    • 5.4.3 Computational Drug Discovery
    • 5.4.4 Medical Treatment Recommendation
    • 5.4.5 Patient Data Processing
    • 5.4.6 Medical Diagnosis Assistance
    • 5.4.7 Converting Paperwork into Digital Data
    • 5.4.8 Automated Report Generation
    • 5.4.9 Hospital Patient Management System
    • 5.4.10 Biomarker Discovery
  • 5.5 Healthcare AI Hardware Forecasts
  • 5.6 Services Revenue Forecasts
  • 5.6.1 Cloud-Based Services Revenue
    • 5.6.2 Services Revenue Breakouts by Service Category
  • 5.7 Conclusions and Recommendations

SECTION 6 Company Directory

SECTION 7 Acronym and Abbreviation List

SECTION 8 Table of Contents

SECTION 9 Table of Charts and Figures

SECTION 10 Scope of Study

TABLE OF CHARTS AND FIGURES

  • Chart 1.1 Healthcare AI Services Revenue by Region, World Markets: 2017-2025
  • Chart 1.2 Healthcare AI Software Revenue, World Markets: 2017-2025
  • Chart 1.3 Top Five Healthcare AI Use Cases Revenue, World Markets: 2017-2025
  • Chart 5.1 Healthcare AI Total Revenue by Segment, World Markets: 2017-2025
  • Chart 5.2 Healthcare AI Total Software, Service, and Hardware Revenue by Region, World Markets: 2017-2025
  • Chart 5.3 Healthcare AI Software Revenue by Region, World Markets: 2017-2025
  • Chart 5.4 Healthcare AI Hardware Revenue by Region, World Markets: 2017-2025
  • Chart 5.5 Healthcare AI Services Revenue by Region, World Markets: 2017-2025
  • Chart 5.6 Healthcare AI Software Revenue by Use Case, World Markets: 2017-2025
  • Chart 5.7 Healthcare AI Software Revenue for Medical Image Analysis by Region, World Markets: 2017-2025
  • Chart 5.8 Healthcare AI Software Revenue for Healthcare VDAs, by Region, World Markets: 2017-2025
  • Chart 5.9 Healthcare AI Software Revenue for Medical Treatment Recommendation by Region, World Markets: 2017-2025
  • Chart 5.10 Healthcare AI Software Revenue for Medical Diagnosis Assistance by Region, World Markets: 2017-2025
  • Chart 5.11 Healthcare AI Software Revenue for Converting Paperwork into Digital Data by Region, World Markets: 2017-2025
  • Chart 5.124 Healthcare AI Software Revenue for Automated Report Generation by Region, World Markets: 2017-2025
  • Chart 5.13 Healthcare AI Software Revenue for Hospital Patient Management Systems by Region, World Markets: 2017-2025
  • Chart 5.14 Healthcare AI Software Revenue for Biomarker Discovery by Region, World Markets: 2017-2025
  • Chart 5.15 Healthcare AI-Driven Hardware Revenue by Product Category, World Markets: 2017-2025
  • Chart 5.16 Healthcare AI-Driven Cloud Services Revenue by Region, World Markets: 2017-2025
  • Chart 5.17 Healthcare AI-Driven Services Revenue by Service Category: World Markets, 2017-2025
  • Chart 10.1 Tractica Research Methodology
  • Table 4.1 AI Companies in the Healthcare Market
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