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市场调查报告书
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1822383

2032 年远端患者监护人工智慧市场预测：按组件、技术、应用、最终用户和地区进行的全球分析

Artificial Intelligence in Remote Patient Monitoring Market Forecasts to 2032 - Global Analysis By Component (AI-Enabled Devices, Software, and Services), Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球远端患者监护人工智慧市场预计在 2025 年达到 25.8 亿美元，到 2032 年将达到 161.3 亿美元，预测期内的复合年增长率为 29.9%。

远端患者监护中的人工智慧是指在远距医疗平台中使用人工智慧工具来监控医院外患者的健康状况。它处理即时医疗数据，识别潜在风险，并提案个人化治疗方案。透过机器学习、预测模型和自动化，人工智慧可以改善患者预后，减少住院次数，加快护理回应速度，并增强慢性病管理。这种方法能够赋能患者和医疗专业人员，同时确保持续、数据驱动且有效率的医疗服务。

据英国政府称，2024 年 7 月至 2025 年 1 月期间，私人公司在人工智慧领域投资了约 2.5 亿美元。

慢性病增多

糖尿病、心血管疾病和呼吸系统疾病等慢性疾病负担日益加重，推动了持续健康监测解决方案的需求。人工智慧驱动的远端患者监护(RPM) 工具正被用于更主动地管理长期疾病并减少再入院率。随着全球人口老化和诊断能力的提高，医疗保健提供者正转向预测分析和个人化介入。穿戴式装置和智慧感测器能够即时追踪生命体征，使临床医生能够更早进行干预。这一趋势正在加速已开发经济体和新兴经济体医疗保健生态系统中 RPM 的采用。

资料安全和隐私问题

HIPAA 和 GDPR 等法规结构要求严格合规，这可能会减缓采用速度并增加营运成本。云端基础和物联网设备的使用会引入漏洞，需要强大的加密和存取控制机制。规模较小的医疗保健提供者通常缺乏有效保护敏感医疗资讯的技术基础设施。基于患者资料进行训练的人工智慧演算法必须遵守道德标准和透明度，才能维护信任。这些与隐私相关的限制限制了可扩展性，并减缓了更广泛的市场渗透。

个人化护理计划和建议

人工智慧主导的远距医疗 (RPM) 系统正在为根据患者独特需求量身定制的个人化护理路径开闢新的可能性。机器学习模型可以分析行为模式、用药依从性和生物特征数据，从而建议及时的干预措施。这种个人化服务正在改善治疗效果，并提高患者在慢性病和急性病护理中的参与度。新平台正在整合语音助理和自然语言处理功能，以提供情境感知的健康指导。预测分析可以实现风险分层和併发症的早期发现，从而减少急诊就诊次数。随着基于价值的照护模式日益普及，个人化远距医疗 (RPM) 正成为医疗保健转型的核心部分。

抵制改变与缺乏数位素养

缺乏数位素养阻碍了智慧医疗设备的有效使用，尤其是在老年人群体中。医疗保健专业人员可能会因为不熟悉人工智慧工具或感知到其复杂性而抵制工作流程的改变。培训计划和用户友好的介面对于弥合这一采用差距至关重要。文化和製度上的惰性可能会减缓远端监控与传统护理模式的融合。如果没有针对性的教育和支持，远距医疗平台可能会被低估，并降低其影响力。

COVID-19的影响

新冠疫情显着加速了全球远端患者监护技术的普及。医院关闭且不堪重负，促使人们转向虚拟护理和人工智慧辅助诊断。远距患者监护工具在管理隔离患者和远端追踪症状方面发挥了关键作用。各国政府和监管机构加快了数位医疗解决方案的核准，促进了创新和部署。疫情后的策略如今强调分散式照护、远端医疗整合以及人工智慧驱动的分流系统。这场危机引发了医疗服务向远距、以数据为中心的转变。

预计人工智慧设备市场在预测期内将占据最大份额

预计人工智慧设备领域将在预测期内占据最大的市场份额，这得益于其在即时健康追踪和决策支援方面的先进功能。这些设备，包括智慧穿戴装置和连网监视器，正越来越多地配备机器学习演算法，以提供预测性洞察。医院和家庭护理提供者正在利用人工智慧检测异常并自动发出警报，以便及时介入。与云端平台和电子健康檔案 (EHR) 的整合正在增强互通性和护理协调性。感测器技术和边缘运算的不断创新正在提升设备的功能性和可靠性。随着人工智慧逐渐融入硬件，预计该领域将在应用和产生收入占据主导。

预测期内，居家照护机构预计将以最高复合年增长率成长

在以患者为中心且注重成本效益的医疗服务模式的推动下，预计居家照护领域将在预测期内实现最高增长率。人工智慧工具正在实现慢性病的远端监控，从而减少频繁就医的需求。智慧家庭健康套件和语音助理的兴起，让远距医疗更便捷、更直观。报销改革和人口老化正在进一步推动居家照护模式的发展。云端基础的仪錶板和行动应用程式正在为看护者提供切实可行的洞察和远端监控功能。随着医疗保健日益分散化，居家照护正成为人工智慧主导的远距医疗扩展的关键前沿。

占比最大的地区：

在预测期内，亚太地区预计将占据最大的市场份额，这得益于快速的医疗数位化和基础设施投资。中国、印度和日本等国家正在扩展远端医疗平台和智慧医院计画。政府计画正透过补贴、先导计画和本地製造业激励措施推动人工智慧的普及。该地区穿戴式医疗设备和基于行动的远距医疗解决方案的普及率正在强劲增长。全球科技公司与本地供应商之间的合作正在加速创新和市场进入。

复合年增长率最高的地区：

在预测期内，北美预计将凭藉其在人工智慧研究和医疗创新领域的领先地位，实现最高的复合年增长率。美国和加拿大正在大力投资智慧医疗基础设施，包括人工智慧分析和远距离诊断。监管机构正在简化数位医疗核准流程，促进远距医疗（RPM）技术的快速商业化。医院正在将人工智慧与物联网和云端平台结合，以优化病患监测和资源配置。优惠的报销政策和消费者对虚拟护理日益增长的需求正在推动其应用。随着精准医疗和预测医学的发展势头强劲，北美将继续为远距医疗的发展树立标竿。

免费客製化服务：

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  • 公司简介
    • 对最多三家其他市场公司进行全面分析
    • 主要企业的SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户兴趣对主要国家进行的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球远端患者监护人工智慧市场（按组件）

  • 支援人工智慧的设备
    • 穿戴式装置
    • 生物感测器
    • 可携式心电图和血糖监测仪
  • 软体
    • 数据分析平台
    • 预测监测工具
  • 服务
    • 远端监控服务
    • 人工智慧整合与支援

6. 全球远端患者监护人工智慧市场（按技术）

  • 机器学习
  • NLP和语音辨识
  • 其他技术

7. 全球远端患者监护人工智慧市场（按应用）

  • 心血管监测
  • 神经系统疾病
  • 糖尿病管理
  • 急性期后恢復
  • 肿瘤学
  • 呼吸系统疾病
  • 其他用途

8. 全球远端患者监护人工智慧市场（按最终用户）

  • 医院和卫生系统
  • 居家照护环境
  • 门诊手术中心（ASC）
  • 病人
  • 其他最终用户

9. 全球远端患者监护人工智慧市场（按地区）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十章：重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十一章 公司概况

  • Koninklijke Philips
  • Medtronic
  • OMRON Healthcare
  • GE HealthCare
  • Biobeat
  • Boston Scientific
  • Dexcom
  • Nihon Kohden
  • F. Hoffmann-La Roche
  • ResMed
  • AliveCor
  • Biotronik
  • Honeywell
  • Masimo
  • Abbott
Product Code: SMRC31137

According to Stratistics MRC, the Global Artificial Intelligence in Remote Patient Monitoring Market is accounted for $2.58 billion in 2025 and is expected to reach $16.13 billion by 2032 growing at a CAGR of 29.9% during the forecast period. Artificial Intelligence in Remote Patient Monitoring involves using AI tools within remote healthcare platforms to oversee patient health beyond hospitals. It processes real-time medical data, identifies potential risks, and suggests tailored treatments. Through machine learning, predictive modelling, and automation, AI boosts patient outcomes, lowers hospital admissions, enables prompt care responses, and enhances chronic condition management. This approach ensures ongoing, data-supported, and efficient healthcare delivery while empowering both patients and healthcare professionals.

According to Gov.UK, private firms invested around USD 250 million investments in AI from July 2024 to January 2025.

Market Dynamics:

Driver:

Growing prevalence of chronic diseases

The increasing burden of chronic illnesses such as diabetes, cardiovascular conditions, and respiratory disorders is fuelling demand for continuous health monitoring solutions. AI-powered remote patient monitoring (RPM) tools are being adopted to manage long-term conditions more proactively and reduce hospital readmissions. As global populations age and diagnostic capabilities improve, healthcare providers are shifting toward predictive analytics and personalized interventions. Wearable devices and smart sensors are enabling real-time tracking of vital signs, empowering clinicians to intervene early. This trend is accelerating RPM adoption across both developed and emerging healthcare ecosystems.

Restraint:

Data security and privacy concerns

Regulatory frameworks such as HIPAA and GDPR require stringent compliance, which can slow deployment and increase operational costs. The use of cloud-based platforms and IoT devices introduces vulnerabilities that demand robust encryption and access controls. Smaller healthcare providers often lack the technical infrastructure to safeguard sensitive health information effectively. AI algorithms trained on patient data must adhere to ethical standards and transparency to maintain trust. These privacy-related constraints are limiting scalability and delaying broader market penetration.

Opportunity:

Personalized care plans and recommendations

AI-driven RPM systems are unlocking new possibilities for individualized care pathways tailored to patient-specific needs. Machine learning models can analyze behavioral patterns, medication adherence, and biometric data to recommend timely interventions. This personalization is improving treatment outcomes and enhancing patient engagement across chronic and post-acute care settings. Emerging platforms are integrating voice assistants and natural language processing to deliver context-aware health coaching. Predictive analytics is enabling risk stratification and early detection of complications, reducing emergency visits. As value-based care models gain traction, personalized RPM is becoming central to healthcare transformation.

Threat:

Resistance to change and lack of digital literacy

Limited digital literacy, especially among elderly populations, hampers effective utilization of smart health devices. Healthcare professionals may resist workflow changes due to unfamiliarity with AI tools and perceived complexity. Training programs and user-friendly interfaces are essential to bridge this adoption gap. Cultural and institutional inertia can delay integration of remote monitoring into traditional care models. Without targeted education and support, RPM platforms risk underutilization and reduced impact.

Covid-19 Impact

The COVID-19 pandemic significantly accelerated the adoption of remote patient monitoring technologies worldwide. Lockdowns and overwhelmed hospitals prompted a shift toward virtual care and AI-assisted diagnostics. RPM tools played a critical role in managing quarantined patients and tracking symptoms remotely. Governments and regulatory bodies fast-tracked approvals for digital health solutions, boosting innovation and deployment. Post-pandemic strategies now emphasize decentralized care, telehealth integration, and AI-driven triage systems. The crisis catalysed a permanent shift toward remote, data-centric healthcare delivery.

The AI-enabled devices segment is expected to be the largest during the forecast period

The AI-enabled devices segment is expected to account for the largest market share during the forecast period, due to its advanced capabilities in real-time health tracking and decision support. These devices, including smart wearables and connected monitors, are increasingly embedded with machine learning algorithms for predictive insights. Hospitals and homecare providers are leveraging AI to detect anomalies and automate alerts for timely intervention. Integration with cloud platforms and EHRs is enhancing interoperability and care coordination. Continuous innovation in sensor technology and edge computing is expanding device functionality and reliability. As AI becomes more embedded in hardware, this segment is set to lead in both adoption and revenue generation.

The homecare settings segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the homecare settings segment is predicted to witness the highest growth rate, driven by the shift toward patient-centric and cost-effective care. AI-powered tools are enabling remote monitoring of chronic conditions, reducing the need for frequent hospital visits. The rise of smart home health kits and voice-enabled assistants is making RPM more accessible and intuitive. Reimbursement reforms and aging demographics are further supporting home-based care models. Cloud-based dashboards and mobile apps are empowering caregivers with actionable insights and remote supervision. As healthcare decentralizes, homecare is emerging as a key frontier for AI-driven RPM expansion.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share supported by rapid healthcare digitization and infrastructure investments. Countries like China, India, and Japan are scaling up telehealth platforms and smart hospital initiatives. Government programs are promoting AI adoption through subsidies, pilot projects, and local manufacturing incentives. The region is witnessing strong uptake of wearable health devices and mobile-based RPM solutions. Collaborations between global tech firms and regional providers are accelerating innovation and market access.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, driven by its leadership in AI research and healthcare innovation. The U.S. and Canada are investing heavily in smart health infrastructure, including AI-powered analytics and remote diagnostics. Regulatory bodies are streamlining digital health approvals, fostering rapid commercialization of RPM technologies. Hospitals are integrating AI with IoT and cloud platforms to optimize patient monitoring and resource allocation. Favorable reimbursement policies and growing consumer demand for virtual care are boosting adoption. As precision medicine and predictive care gain momentum, North America continues to set the benchmark for RPM evolution.

Key players in the market

Some of the key players profiled in the Artificial Intelligence in Remote Patient Monitoring Market include Koninklijke Philips, Medtronic, OMRON Healthcare, GE HealthCare, Biobeat, Boston Scientific, Dexcom, Nihon Kohden, F. Hoffmann-La Roche, ResMed, AliveCor, Biotronik, Honeywell, Masimo, and Abbott.

Key Developments:

In September 2025, Royal Philips and Masimo announced that the two companies have renewed their multi-year strategic collaboration, marking a fresh chapter in their long-standing partnership. With a shared commitment to innovation and expanding access to high-quality, connected care, the two companies are taking a bold new approach in accelerating the development and delivery of next-generation patient monitoring solutions.

In April 2025, Medtronic plc announced it has submitted 510(k) applications to the U.S. Food and Drug Administration (FDA) seeking clearance for an interoperable pump. FDA clearance of this pump would pave the way for system integration with a continuous glucose monitoring (CGM) sensor based on Abbott's most advanced CGM platform.

Components Covered:

  • AI-Enabled Devices
  • Software
  • Services

Technologies Covered:

  • Machine Learning
  • NLP & Speech Recognition
  • Other Technologies

Applications Covered:

  • Cardiovascular Monitoring
  • Neurological Disorders
  • Diabetes Management
  • Post-Acute Recovery
  • Oncology
  • Respiratory Disorders
  • Other Applications

End Users Covered:

  • Hospitals & Health Systems
  • Homecare Settings
  • Ambulatory Surgical Centers (ASCs)
  • Patients
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Artificial Intelligence in Remote Patient Monitoring Market, By Component

  • 5.1 Introduction
  • 5.2 AI-Enabled Devices
    • 5.2.1 Wearables
    • 5.2.2 Biosensors
    • 5.2.3 Portable ECG & Glucose Monitors
  • 5.3 Software
    • 5.3.1 Data Analytics Platforms
    • 5.3.2 Predictive Monitoring Tools
  • 5.4 Services
    • 5.4.1 Remote Monitoring Services
    • 5.4.2 AI Integration & Support

6 Global Artificial Intelligence in Remote Patient Monitoring Market, By Technology

  • 6.1 Introduction
  • 6.2 Machine Learning
  • 6.3 NLP & Speech Recognition
  • 6.4 Other Technologies

7 Global Artificial Intelligence in Remote Patient Monitoring Market, By Application

  • 7.1 Introduction
  • 7.2 Cardiovascular Monitoring
  • 7.3 Neurological Disorders
  • 7.4 Diabetes Management
  • 7.5 Post-Acute Recovery
  • 7.6 Oncology
  • 7.7 Respiratory Disorders
  • 7.8 Other Applications

8 Global Artificial Intelligence in Remote Patient Monitoring Market, By End User

  • 8.1 Introduction
  • 8.2 Hospitals & Health Systems
  • 8.3 Homecare Settings
  • 8.4 Ambulatory Surgical Centers (ASCs)
  • 8.5 Patients
  • 8.6 Other End Users

9 Global Artificial Intelligence in Remote Patient Monitoring Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Koninklijke Philips
  • 11.2 Medtronic
  • 11.3 OMRON Healthcare
  • 11.4 GE HealthCare
  • 11.5 Biobeat
  • 11.6 Boston Scientific
  • 11.7 Dexcom
  • 11.8 Nihon Kohden
  • 11.9 F. Hoffmann-La Roche
  • 11.10 ResMed
  • 11.11 AliveCor
  • 11.12 Biotronik
  • 11.13 Honeywell
  • 11.14 Masimo
  • 11.15 Abbott

List of Tables

  • Table 1 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By AI-Enabled Devices (2024-2032) ($MN)
  • Table 4 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Wearables (2024-2032) ($MN)
  • Table 5 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Biosensors (2024-2032) ($MN)
  • Table 6 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Portable ECG & Glucose Monitors (2024-2032) ($MN)
  • Table 7 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Software (2024-2032) ($MN)
  • Table 8 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Data Analytics Platforms (2024-2032) ($MN)
  • Table 9 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Predictive Monitoring Tools (2024-2032) ($MN)
  • Table 10 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Services (2024-2032) ($MN)
  • Table 11 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Remote Monitoring Services (2024-2032) ($MN)
  • Table 12 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By AI Integration & Support (2024-2032) ($MN)
  • Table 13 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Technology (2024-2032) ($MN)
  • Table 14 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Machine Learning (2024-2032) ($MN)
  • Table 15 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By NLP & Speech Recognition (2024-2032) ($MN)
  • Table 16 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 17 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Application (2024-2032) ($MN)
  • Table 18 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Cardiovascular Monitoring (2024-2032) ($MN)
  • Table 19 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Neurological Disorders (2024-2032) ($MN)
  • Table 20 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Diabetes Management (2024-2032) ($MN)
  • Table 21 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Post-Acute Recovery (2024-2032) ($MN)
  • Table 22 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Oncology (2024-2032) ($MN)
  • Table 23 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Respiratory Disorders (2024-2032) ($MN)
  • Table 24 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 25 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By End User (2024-2032) ($MN)
  • Table 26 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Hospitals & Health Systems (2024-2032) ($MN)
  • Table 27 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Homecare Settings (2024-2032) ($MN)
  • Table 28 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Ambulatory Surgical Centers (ASCs) (2024-2032) ($MN)
  • Table 29 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Patients (2024-2032) ($MN)
  • Table 30 Global Artificial Intelligence in Remote Patient Monitoring Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.