预测疾病分析市场、机会、成长动力、产业趋势分析与预测，2024-2032 年

全球预测疾病分析市场预计2023 年将价值25 亿美元，预计2024 年至2032 年复合年增长率为21.7%。进步的关注。

医疗保健领域对精准医疗和数据驱动决策的需求加速了预测分析解决方案的采用。这些技术使医疗保健提供者能够透过利用资料预测未来的健康事件来预见患者的结果、完善治疗计划并降低医疗成本。例如，2024 年 4 月，克莱姆森大学的研究人员正在探索用于精准医疗的人工智慧技术，根据患者的基因图谱检查药物机制。

一个显着的趋势是基于云端的解决方案的兴起。云端部署提供可扩展性、灵活性和成本效益，使医疗保健组织能够管理大量资料并远端存取分析工具，从而增强资料整合和即时分析。

整个预测疾病分析产业根据组件、部署模式、最终用途和区域进行细分。

软体部分包括用于健康资料分析和预测见解的工具和平台，到 2023 年将创造 20 亿美元的收入。由于对与现有医疗保健系统整合的高级分析的需求，预计该细分市场将保持重要的市场份额。资料视觉化、风险评估和结果预测等功能使该软体对于医疗保健组织至关重要。 2024 年 7 月，Cardio Diagnostics Holdings Inc. 推出了 CDIO.AI 网路解决方案，具有人工智慧驱动的心血管疾病功能。

该市场按部署模式分为本地和云，到 2023 年，本地细分市场将达到 15 亿美元。方面的大量投资。具有严格资料隐私要求的组织更喜欢本地解决方案，以保持对敏感健康资讯的控制并确保法规遵循。例如，2018 年 3 月，NVIDIA Healthcare 推出了针对医疗技术、药物发现和数位健康的生成式 AI 微服务。

北美预测疾病分析市场到2023 年收入将达到9.191 亿美元，2024 年至2032 年复合年增长率将达到20.9%。所推动的。预测分析有助于识别高风险患者、优化治疗计划并减少不必要的就诊。快速的技术进步和对复杂资料分析平台的存取进一步加速了采用，利用人工智慧和机器学习来实现准确的预测和可行的见解。

目录

第 1 章：方法与范围

第 2 章：执行摘要

第 3 章：产业洞察

• 产业生态系统分析
• 产业影响力
  • 成长动力
    • 越来越注重简化医疗流程
    • 对预防性医疗保健的日益关注
    • 人工智慧和机器学习技术的进步以及患者治疗效果的改善
  • 产业陷阱与挑战
    • 资料隐私和安全问题
• 成长潜力分析
• 监管环境
• 创新格局
• 波特的分析
• PESTEL分析
• 未来市场趋势
• 差距分析

第 4 章：竞争格局

• 介绍
• 公司矩阵分析
• 主要参与者竞争分析
• 竞争定位矩阵
• 战略仪表板

第 5 章：市场估计与预测：按组成部分，2021 - 2032 年

• 主要趋势
• 软体
• 服务

第 6 章：市场估计与预测：按部署模式，2021 - 2032 年

• 主要趋势
• 本地
• 云

第 7 章：市场估计与预测：按最终用途，2021 - 2032 年

• 主要趋势
• 医疗保健付款人
• 医疗保健提供者
• 其他最终用户

第 8 章：市场估计与预测：按地区划分，2021 - 2032 年

• 主要趋势
• 北美洲
  • 我们
  • 加拿大
• 欧洲
  • 德国
  • 英国
  • 法国
  • 西班牙
  • 义大利
  • 荷兰
  • 欧洲其他地区
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 澳洲
  • 韩国
  • 亚太地区其他地区
• 拉丁美洲
  • 巴西
  • 墨西哥
  • 阿根廷
  • 拉丁美洲其他地区
• 中东和非洲
  • 南非
  • 沙乌地阿拉伯
  • 阿联酋
  • 中东和非洲其他地区

第 9 章：公司简介

• Allscripts Healthcare Solutions Inc.
• Anaconda Inc.
• Apixio Inc.
• Epic System Corporation
• Health Catalyst
• IBM
• McKesson Corporation
• MedeAnalytics, Inc.
• Microsoft Corporation
• Optum
• Oracle
• Philips Healthcare
• SAS
• Siemens Healthineers

The Global Predictive Disease Analytics Market, valued at USD 2.5 billion in 2023, is projected to grow at a CAGR of 21.7% from 2024 to 2032. This growth is driven by a focus on streamlining healthcare processes, preventive healthcare, and advancements in AI and machine learning technologies.

The demand for precision medicine and data-driven decision-making in healthcare accelerates the adoption of predictive analytics solutions. These technologies enable healthcare providers to foresee patient outcomes, refine treatment plans, and reduce healthcare costs by leveraging data to predict future health events. For example, in April 2024, researchers at Clemson University are exploring AI technologies for precision medicine, examining drug mechanisms alongside patients' genetic profiles.

A notable trend is the rise in cloud-based solutions. Cloud deployment offers scalability, flexibility, and cost-effectiveness, allowing healthcare organizations to manage large data volumes and access analytics tools remotely, enhancing data integration and real-time analysis.

The overall predictive disease analytics industry is segmented based on component, deployment mode, end-use, and region.

The software segment, which generated USD 2 billion in 2023, includes tools and platforms for health data analysis and predictive insights. This segment is expected to maintain a significant market share due to the demand for advanced analytics that integrate with existing healthcare systems. Features like data visualization, risk assessment, and outcome prediction make the software essential for healthcare organizations. In July 2024, Cardio Diagnostics Holdings Inc. launched its CDIO.AI web-solution with AI-driven functionalities for cardiovascular diseases.

The market, categorized by deployment mode into on-premises and cloud, saw the on-premises segment leading with USD 1.5 billion in 2023. On-premises deployment, which installs predictive analytics software within an organization's IT environment, offers control and customization but requires significant investment in hardware and maintenance. Organizations with stringent data privacy requirements prefer on-premises solutions to maintain control over sensitive health information and ensure regulatory compliance. For instance, in March 2018, NVIDIA Healthcare introduced generative AI microservices for medtech, drug discovery, and digital health.

North America predictive disease analytics market, with a revenue of USD 919.1 million in 2023, is set to grow at a CAGR of 20.9% from 2024 to 2032. The region's demand for predictive disease analytics is driven by a shift towards value-based healthcare and cost containment. Predictive analytics helps identify high-risk patients, optimize treatment plans, and reduce unnecessary hospital visits. Rapid technological advancements and access to sophisticated data analytics platforms further accelerate adoption, leveraging AI and machine learning for accurate predictions and actionable insights.

Table of Contents

Chapter 1 Methodology and Scope

• 1.1 Market scope and definitions
• 1.2 Research design
  • 1.2.1 Research approach
  • 1.2.2 Data collection methods
• 1.3 Base estimates and calculations
  • 1.3.1 Base year calculation
  • 1.3.2 Key trends for market estimation
• 1.4 Forecast model
• 1.5 Primary research and validation
  • 1.5.1 Primary sources
  • 1.5.2 Data mining sources

Chapter 2 Executive Summary

• 2.1 Industry 360° synopsis

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Industry impact forces
  • 3.2.1 Growth drivers
    • 3.2.1.1 Increasing focus on streamlining of healthcare processes
    • 3.2.1.2 Rising focus on preventive healthcare
    • 3.2.1.3 Advancements in AI and machine learning technologies coupled with improved patient outcomes
  • 3.2.2 Industry pitfalls and challenges
    • 3.2.2.1 Data privacy and security concerns
• 3.3 Growth potential analysis
• 3.4 Regulatory landscape
• 3.5 Innovation landscape
• 3.6 Porter's analysis
• 3.7 PESTEL analysis
• 3.8 Future market trends
• 3.9 Gap analysis

Chapter 4 Competitive Landscape, 2023

• 4.1 Introduction
• 4.2 Company matrix analysis
• 4.3 Competitive analysis of major key players
• 4.4 Competitive positioning matrix
• 4.5 Strategy dashboard

Chapter 5 Market Estimates and Forecast, By Component, 2021 - 2032 ($ Mn)

• 5.1 Key trends
• 5.2 Software
• 5.3 Services

Chapter 6 Market Estimates and Forecast, By Deployment Mode, 2021 - 2032 ($ Mn)

• 6.1 Key trends
• 6.2 On-premises
• 6.3 Cloud

Chapter 7 Market Estimates and Forecast, By End-use, 2021 - 2032 ($ Mn)

• 7.1 Key trends
• 7.2 Healthcare payers
• 7.3 Healthcare providers
• 7.4 Other end-users

Chapter 8 Market Estimates and Forecast, By Region, 2021 - 2032 ($ Mn)

• 8.1 Key trends
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 UK
  • 8.3.3 France
  • 8.3.4 Spain
  • 8.3.5 Italy
  • 8.3.6 Netherlands
  • 8.3.7 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 Japan
  • 8.4.3 India
  • 8.4.4 Australia
  • 8.4.5 South Korea
  • 8.4.6 Rest of Asia Pacific
• 8.5 Latin America
  • 8.5.1 Brazil
  • 8.5.2 Mexico
  • 8.5.3 Argentina
  • 8.5.4 Rest of Latin America
• 8.6 Middle East and Africa
  • 8.6.1 South Africa
  • 8.6.2 Saudi Arabia
  • 8.6.3 UAE
  • 8.6.4 Rest of Middle East and Africa

Chapter 9 Company Profiles

• 9.1 Allscripts Healthcare Solutions Inc.
• 9.2 Anaconda Inc.
• 9.3 Apixio Inc.
• 9.4 Epic System Corporation
• 9.5 Health Catalyst
• 9.6 IBM
• 9.7 McKesson Corporation
• 9.8 MedeAnalytics, Inc.
• 9.9 Microsoft Corporation
• 9.10 Optum
• 9.11 Oracle
• 9.12 Philips Healthcare
• 9.13 SAS
• 9.14 Siemens Healthineers