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市场调查报告书
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1371904

到 2030 年远端患者监护领域人工智慧市场预测：按产品、解决方案、技术和地区分類的全球分析

Artificial Intelligence In Remote Patient Monitoring Market Forecasts to 2030 - Global Analysis By Product (Vital Monitors, Special Monitors and Other Products), Solution, Technology 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，2023 年全球远端患者监护人工智慧市场规模达 14 亿美元，预计预测期内年复合成长率为 27.8%，到 2030 年将达到 77 亿美元。

远端患者监护(RPM)，有时也称为人工智慧 (AI)，是使用人工智慧和相关技术远端监测患者健康状况的过程。透过利用各种感测器、小工具和数数位平台，该技术使医疗保健专业人员能够追踪患者的健康状况，而无需定期亲自就诊。人工智慧透过自动化资料分析、提供预测性见解以及实现更个人化和主动的医疗保健来提高 RPM。当发现重大变化或异常时，人工智慧驱动的 RPM 系统可以向医疗保健提供者发送警报和通知。这些通知允许及时干预。

根据美国疾病管制与预防中心 (CDC) 的数据，美国有超过 1,820 万名 20 岁及以上的成年人患有冠状动脉疾病。

提高药物依从性

在远端患者监护(RPM) 的背景下，人工智慧 (AI) 可以显着提高用药依从性。医疗保健中的一个主要问题是药物不依从性，这会降低治疗效果并增加支出。在人工智慧的支援下，RPM 系统可以透过各种媒体（包括行动应用程式、简讯和电子邮件）向患者发送个人化用药提醒。患者会发现更容易记住按照指示服药，根据他们的服药时间表量身定制。为了製定个体化的药物计划，人工智慧可以检查患者的医学背景、当前的健康状况和用药习惯。此类计划透过考虑给药频率、药物交互作用和潜在副作用等因素，确保患者获得最佳的治疗建议。因此，所有上述要素都将在整个预测期内推动市场成长。

资料安全和隐私

患者健康资讯极为敏感，披露这些资讯可能会产生不良后果。 RPM 中的 AI 依赖患者资料的收集和传输，因此容易受到入侵和资料外洩。由于加密技术薄弱和安全措施诈欺，患者资讯可能容易受到未经授权的访问，从而使患者隐私面临风险，因为资料可能被未经授权的人员访问。因此，除非经过精心规划和维护，人工智慧系统可能会为不同的病患小组提供不同程度的护理和诊断准确性，从而加剧医疗保健不平等。因此，上述所有要素都阻碍了市场的成长。

降低成本、经济

人工智慧驱动的远端监控可以检测健康状况下降的早期预警并实现快速介入。这减少了住院的需要，特别是慢性病管理和术后护理。透过避免因非紧急问题而去急诊室，透过远端监控进行早期诊断和介入可以减少对紧急医疗服务的需求。长期成本节约和改善的医疗结果使人工智慧远端监控成为寻求最佳化医疗服务和降低成本的医疗保健提供者和付款人的有吸引力的选择。

基于人工智慧的远端监控解决方案在低收入和中等收入国家尚未得到充分采用

人工智慧 (AI) 已成为医疗保健行业的强大工具，有可能彻底改变患者照护、降低成本并改善结果。虽然基于人工智慧的 RPM 解决方案在高所得国家迅速普及，但在中低收入国家 (LMIC) 的采用率仍然相对较低。中低收入国家的医疗保健预算通常很紧张，因此分配资金来购买和实施昂贵的基于人工智慧的 RPM 系统可能很困难。在一些低收入和中等收入国家，拥有足够的医院、诊所和经过必要培训的医疗专业人员可能很困难，阻碍了市场成长。

COVID-19 的影响

COVID-19 的爆发促进了远端患者监测设备的使用。该国政府在疫情期间实施了旅行限制，迫切需要实施远端患者监护服务。此外，医疗保健公司透过提供大量用于远距疾病监测的医疗设备来快速应对 COVID-19 情况。例如，为了减少患者互动并远端管理健康，美国食品药物管理局(美国 FDA) 于 2020 年 4 月核准Dexcom 和 Abbott 在医院提供连续血糖监测设备。

生命监视器细分市场预计将在预测期内成为最大的细分市场

在生命监视器领域，搭载人工智慧的生命征象监视器可以远端评估患者的健康状况，目的是持续或零星地收集和评估患者的各种生理指标，预计将有良好的增长。这些监测仪持续或零星地收集和评估患者的各种生理指标，使医疗保健专业人员能够及早干预并在适当的时候获得重要的见解。Masu。为了追踪患者的心率，人工智慧系统可以检查心电图 (ECG)资料或脉搏波形。如果您的心臟有心律不整，则可以使用袖带装置或光电血压计 (PPG) 等非侵入性技术来监测收缩压和舒张压。因此，重要的监视器部门正在推动市场的成长。

机器学习领域预计在预测期内年复合成长率最高

由于人工智慧的一个领域机器学习（ML）显着提高了 RPM 系统的有效性和效率，因此机器学习领域预计在预测期内将出现最高的年复合成长率年增长率。大量患者资料，包括生命征象、感测器读数和电子健康记录，均由机器学习演算法进行专业处理。这些演算法可以发现人类看护者可能会错过的模式和趋势。例如，机器学习可以识别生命征象的细微变化，并发出健康状况恶化或潜在紧急情况的信号。根据历史资料，机器学习模型可以预测患者的治疗结果。透过检查患者记录和病历，这些模型可以预测疾病进展、再入院和不利事件的可能性。这使得医疗保健专业人员能够提供个人化的护理计划并主动干预。

占比最大的地区：

由于有利的法律​​体系、充足的医疗基础设施以及人工智慧设备的快速采用，预计欧洲在预测期内将占据最大的市场占有率。此外，这些人工智慧辅助监测设备在该地区的部署得到了公司之间策略联盟的支持，为患者提供完整的远端患者监护，这将提高接受度。例如，MTech Mobility 和 GenieMD 于 2021 年 8 月签订了合作伙伴协议，透过为客户提供广泛的远端患者监护选项来加强该地区的市场成长。

复合年复合成长率最高的地区：

预计北美在预测期内将经历最高的年复合成长率。这是因为许多变数正在推动北美的持续扩张，包括高龄化、慢性病的增加以及对负担得起的医疗保健解决方案的需求。 COVID-19 大流行也加速了远距患者监护技术的引入。北美的许多公司正在积极致力于开发人工智慧主导的应用程序，用于远端患者监护。其中包括知名的医疗保健IT公司以及专注于人工智慧的新兴医疗保健公司。人工智慧主导的RPM 解决方案与北美远端医疗服务的扩展是相辅相成的。

提供免费客製化：

订阅此报告的客户将收到以下免费自订选项之一：

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
    • 主要企业SWOT分析（最多3家企业）
  • 区域分割
    • 根据客户兴趣对主要国家的市场估计、预测和年复合成长率（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1章执行摘要

第2章前言

  • 概述
  • 利害关係人
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 调查来源
    • 主要调查来源
    • 二次调查来源
    • 先决条件

第3章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 产品分析
  • 技术分析
  • 应用分析
  • 新兴市场
  • 新型冠状病毒感染疾病（COVID-19）的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第5章远距病患监护市场中的全球人工智慧：副产品

  • 生命监测仪
    • 脑部监视器
    • 脉搏血氧仪
    • 温度监控器
    • 呼吸监测仪
    • 血压监测仪
    • 心率监测器
  • 特殊监视器
    • 血糖监测仪
    • 多参数监视器
    • 凝血酶原监测仪
    • 心律监测器
    • 胎心率监测仪
    • 麻醉监控器
  • 其他产品

第6章远距患者监护市场中的全球人工智慧：按解决方案

  • 软体
  • 硬体
  • 服务

第7章远距病患监护市场中的全球人工智慧：按技术分类

  • 自然语言处理
  • 机器学习
  • 如何联络方式
  • 语音辨识

第8章全球人工智慧在远距患者监护市场的应用：按应用分类

  • 糖尿病
  • 呼吸系统的问题
  • 体重管理和健身监测
  • 癌症
  • 脱水
  • 心血管疾病
  • 睡眠失调
  • 病毒感染
  • 其他用途

第11章全球人工智慧远距患者监护市场：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

第12章进展

  • 合约、伙伴关係、协作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第13章公司简介

  • Koninklijke Philips NV
  • Medtronic
  • GE Healthcare
  • Abbott Laboratories
  • Resideo Life Care Solutions
  • Cardiomo Care, Inc.
  • Current Health Limited
  • Biofourmis Inc.
  • CU-BX Automotive Technologies Ltd.
  • AiCure, LLC
  • Binah.ai
  • ChroniSense Medical, Ltd.
  • Huma Therapeutics Limited
  • Feebris Ltd.
  • iRhythm Technologies, Inc.
  • iHealth Labs, Inc.
  • Gyant.com, Inc.
  • Myia Labs Inc.
  • iBeat, Inc.
  • Neteera Technologies Ltd.
  • VivaLNK Inc.
Product Code: SMRC23961

According to Stratistics MRC, the Global Artificial Intelligence In Remote Patient Monitoring Market is accounted for $1.4 billion in 2023 and is expected to reach $7.7 billion by 2030 growing at a CAGR of 27.8% during the forecast period. Remote patient monitoring (RPM), sometimes known as artificial intelligence (AI), is the process of remotely monitoring a patient's health using AI and related technologies. By utilizing a variety of sensors, gadgets, and digital platforms, this technology enables healthcare professionals to track a patient's health state without the need for regular in-person visits. By automating data analysis, offering predictive insights, and enabling more individualized and pro-active healthcare, AI improves RPM. When significant changes or anomalies are found, RPM systems with AI can send alerts and notifications to healthcare providers. Timely intervention is made possible by these notifications.

According to the Centers for Disease Control and Prevention (CDC), more than 18.2 million adults aged 20 and above have coronary artery disease in the U.S.

Market Dynamics:

Driver:

Improved medication adherence

In the context of Remote Patient Monitoring (RPM), artificial intelligence (AI) significantly improves medication adherence. A major problem in healthcare is medication non-adherence, which reduces the efficacy of treatment and raises expenditures. Personalized medication reminders can be sent to patients by AI-powered RPM systems via a variety of media, including mobile apps, text messages, or emails. The patient will find it easier to remember to take their meds as directed, which are customized to the patient's medication schedule. To develop individualized pharmaceutical plans, AI can examine a patient's medical background, present health, and drug routine. These plans ensure that patients receive the best possible treatment recommendations by taking into account elements like dose frequency, pharmaceutical interactions, and potential side effects. Hence all the above factors boost the market growth throughout the extrapolated period.

Restraint:

Data security and privacy

Patient health information is extremely sensitive, and any disclosure of this information may have negative effects. AI in RPM is susceptible to intrusions and data breaches since it relies on gathering and transferring patient data. Patient information may be vulnerable to unauthorized access due to weak encryption techniques or insufficient security measures and the data could potentially be accessed by unauthorized people, putting patients' privacy at risk. RPM's AI algorithms could pick up biases from the training data, which could result in disparate healthcare results for various racial and ethnic groups thus AI systems may worsen healthcare inequities by offering varying degrees of care or diagnostic accuracy for various patient groups if they are not carefully planned and maintained. Thus, all the above factors hamper the growth of the market.

Opportunity:

Cost saving and economical

Remote monitoring driven by AI can spot early warning indications of health decline, enabling prompt interventions. This lessens the need for hospital hospitalizations, especially for the management of chronic diseases and post-operative care. By preventing trips to the emergency department for non-urgent problems, early diagnosis and intervention through remote monitoring can lessen the demand on emergency healthcare services. The long-term cost savings and improved healthcare outcomes make AI in Remote Monitoring an appealing choice for healthcare providers and payers looking to optimize healthcare delivery and cut costs, even though the initial investment in AI technology and infrastructure may be necessary.

Threat:

Low and middle-income countries lack the deployment of artificial intelligence-based remote monitoring solutions

Artificial intelligence (AI) has become a potent tool in the healthcare industry with the potential to revolutionize patient care, cut costs, and enhance outcomes. While AI-based RPM solutions have quickly taken off in high-income nations, their adoption in low- and middle-income nations (LMICs) is still relatively low. The allocation of funding for the purchase and deployment of AI-based RPM systems, which can be expensive, might be difficult in LMICs because healthcare budgets there are frequently tight. Having sufficient hospitals, clinics, and medical professionals with the necessary training can be difficult in some low- and middle-income nations which impedes the market growth.

COVID-19 Impact

The COVID-19 epidemic has pushed the use of gadgets for patient remote monitoring due to the country's government's travel limitations during the pandemic, implementing remote patient monitoring services became urgently necessary. Additionally, healthcare businesses responded quickly to the COVID-19 scenario by providing a huge number of medical gadgets for remote sickness monitoring. For instance, in order to reduce patient interaction and manage health remotely, the U.S. Food and Drug Administration (U.S. FDA) approved Dexcom and Abbott to offer continuous glucose monitoring devices in hospitals in April 2020.

The vital monitors segment is expected to be the largest during the forecast period

The vital monitors segment is estimated to have a lucrative growth, as remote assessment of a patient's health status is made possible by AI-powered vital sign monitors, which are meant to continuously or sporadically collect and evaluate a variety of physiological indicators from patients. When appropriate, these monitors can let healthcare professionals intervene early and with significant insights. To track a patient's heart rate, AI systems might examine electrocardiogram (ECG) data or pulse waveforms. It is possible to monitor both systolic and diastolic blood pressure using cuff-based devices or non-invasive techniques like photoplethysmography (PPG) when there are irregularities in heart rhythm. Hence vital monitor segment contributes to the enhancing growth of the market.

The machine learning segment is expected to have the highest CAGR during the forecast period

The machine learning segment is anticipated to witness the highest CAGR growth during the forecast period, as the effectiveness and efficiency of RPM systems are significantly improved by machine learning (ML), a branch of artificial intelligence. Large amounts of patient data, including vital signs, sensor readings, and electronic medical records, are processed expertly by machine learning algorithms. These algorithms can spot patterns and trends that human caregivers might overlook. For instance, ML can identify small alterations in vital signs that signal a person's health is worsening or a potential medical emergency. Based on past data, ML models can predict the outcomes of patients. These models can forecast disease progression, hospital readmissions, or the likelihood of adverse events by studying patient records and medical histories. This enables healthcare professionals to deliver individualized care plans and intervene pro-actively.

Region with largest share:

Europe is projected to hold the largest market share during the forecast period owing to good legislative conditions, the presence of a sufficient healthcare infrastructure, and the quick uptake of the AI devices, Europe retained the largest share in the market. Additionally, the rollout of these AI assisted monitoring devices in the region is being aided by strategic alliances amongst the businesses to offer patients complete remote patient monitoring, which will increase acceptance. For instance, MTech Mobility and GenieMD signed a partnership agreement in August 2021 to offer their customers a wide range of remote patient monitoring options which are enhancing the market growth in this region.

Region with highest CAGR:

North America is projected to have the highest CAGR over the forecast period, owing to a number of variables, such as an aging population, an increase in chronic diseases, and the demand for affordable healthcare solutions, have contributed to North America's continuous expansion. The COVID-19 epidemic has also sped up the introduction of technologies for remote patient monitoring. A number of businesses in North America are actively working to develop AI-driven applications for remote patient monitoring. These include both well-known healthcare IT firms and emerging AI-focused healthcare businesses. AI-driven RPM solutions and the expansion of telehealth services in North America work in harmony.

Key players in the market

Some of the key players profiled in the Artificial Intelligence In Remote Patient Monitoring Market include: Koninklijke Philips N.V., Medtronic, GE Healthcare, Abbott Laboratories, Resideo Life Care Solutions, Cardiomo Care, Inc., Current Health Limited, Biofourmis Inc., CU-BX Automotive Technologies Ltd., AiCure, LLC, Binah.ai, ChroniSense Medical, Ltd., Huma Therapeutics Limited, Feebris Ltd., iRhythm Technologies, Inc., iHealth Labs, Inc., Gyant.com, Inc., Myia Labs Inc., iBeat, Inc., Neteera Technologies Ltd. and VivaLNK Inc.

Key Developments:

In September 2023, Medtronic Diabetes announces CE Mark for new Simplera™ CGM with disposable all-in-one design. The company's newest no-fingerstick sensor does not require over tape and is seamlessly integrated with the InPen™ smart insulin pen, which provides real-time, personalized dosing guidance

In June 2023, Medtronic presents new data on MiniMed™ 780G system on fixed meal dosing and real-world Time in Range across wide variety of users. hese latest results were presented this weekend at the 83rd American Diabetes Association (ADA) Scientific Sessions in San Diego, CA.

In June 2023, Philips and Masimo introduce new, advanced monitoring capabilities to Philips high acuity patient monitors. The latest extension of Masimo and Philips' ongoing collaboration will help enable clinicians to make quick and informed decisions without the need for additional monitoring equipment.

In May 2023, Philips launches AI-powered CT system to accelerate routine radiology and high-volume screening programs. Powered by AI, the Philips CT 3500 includes a range of image-reconstruction and workflow-enhancing features that help to deliver the consistency, speed, and first-time-right image quality

Products Covered:

  • Vital Monitors
  • Special Monitors
  • Other Products

Solutions Covered:

  • Software
  • Hardware
  • Services

Technologies Covered:

  • Natural Language Processing
  • Machine Learning
  • Querying Method
  • Speech Recognition

Applications Covered:

  • Diabetes
  • Respiratory Issues
  • Weight Management & Fitness Monitoring
  • Cancer
  • Dehydration
  • Cardiovascular Diseases
  • Sleep Disorder
  • Viral Infection
  • Other Applications

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 2021, 2022, 2023, 2026, and 2030
  • 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 Product Analysis
  • 3.7 Technology Analysis
  • 3.8 Application 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 Product

  • 5.1 Introduction
  • 5.2 Vital Monitors
    • 5.2.1 Brain Monitor
    • 5.2.2 Pulse Oximeter
    • 5.2.3 Temperature Monitor
    • 5.2.4 Respiratory Monitor
    • 5.2.5 Blood Pressure Monitor
    • 5.2.6 Heart Rate Monitor
  • 5.3 Special Monitors
    • 5.3.1 Blood Glucose Monitor
    • 5.3.2 Multi-Parameter Monitors
    • 5.3.3 Prothrombin Monitors
    • 5.3.4 Cardiac Rhythm Monitor
    • 5.3.5 Fetal Heart Rate Monitor
    • 5.3.6 Anaesthesia Monitors
  • 5.4 Other Products

6 Global Artificial Intelligence In Remote Patient Monitoring Market, By Solution

  • 6.1 Introduction
  • 6.2 Software
  • 6.3 Hardware
  • 6.4 Services

7 Global Artificial Intelligence In Remote Patient Monitoring Market, By Technology

  • 7.1 Introduction
  • 7.2 Natural Language Processing
  • 7.3 Machine Learning
  • 7.4 Querying Method
  • 7.5 Speech Recognition

8 Global Artificial Intelligence In Remote Patient Monitoring Market, By Application

  • 8.1 Introduction
  • 8.2 Diabetes
  • 8.3 Respiratory Issues
  • 8.4 Weight Management & Fitness Monitoring
  • 8.5 Cancer
  • 8.6 Dehydration
  • 8.7 Cardiovascular Diseases
  • 8.8 Sleep Disorder
  • 8.9 Viral Infection
  • 8.10 Other Applications

11 Global Artificial Intelligence In Remote Patient Monitoring Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Koninklijke Philips N.V.
  • 13.2 Medtronic
  • 13.3 GE Healthcare
  • 13.4 Abbott Laboratories
  • 13.5 Resideo Life Care Solutions
  • 13.6 Cardiomo Care, Inc.
  • 13.7 Current Health Limited
  • 13.8 Biofourmis Inc.
  • 13.9 CU-BX Automotive Technologies Ltd.
  • 13.10 AiCure, LLC
  • 13.11 Binah.ai
  • 13.12 ChroniSense Medical, Ltd.
  • 13.13 Huma Therapeutics Limited
  • 13.14 Feebris Ltd.
  • 13.15 iRhythm Technologies, Inc.
  • 13.16 iHealth Labs, Inc.
  • 13.17 Gyant.com, Inc.
  • 13.18 Myia Labs Inc.
  • 13.19 iBeat, Inc.
  • 13.20 Neteera Technologies Ltd.
  • 13.21 VivaLNK Inc.

List of Tables

  • Table 1 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Product (2021-2030) ($MN)
  • Table 3 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Vital Monitors (2021-2030) ($MN)
  • Table 4 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Brain Monitor (2021-2030) ($MN)
  • Table 5 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Pulse Oximeter (2021-2030) ($MN)
  • Table 6 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Temperature Monitor (2021-2030) ($MN)
  • Table 7 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Respiratory Monitor (2021-2030) ($MN)
  • Table 8 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Blood Pressure Monitor (2021-2030) ($MN)
  • Table 9 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Heart Rate Monitor (2021-2030) ($MN)
  • Table 10 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Special Monitors (2021-2030) ($MN)
  • Table 11 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Blood Glucose Monitor (2021-2030) ($MN)
  • Table 12 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Multi-Parameter Monitors (2021-2030) ($MN)
  • Table 13 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Prothrombin Monitors (2021-2030) ($MN)
  • Table 14 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Cardiac Rhythm Monitor (2021-2030) ($MN)
  • Table 15 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Fetal Heart Rate Monitor (2021-2030) ($MN)
  • Table 16 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Anaesthesia Monitors (2021-2030) ($MN)
  • Table 17 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Other Products (2021-2030) ($MN)
  • Table 18 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Solution (2021-2030) ($MN)
  • Table 19 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Software (2021-2030) ($MN)
  • Table 20 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Hardware (2021-2030) ($MN)
  • Table 21 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Services (2021-2030) ($MN)
  • Table 22 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Technology (2021-2030) ($MN)
  • Table 23 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Natural Language Processing (2021-2030) ($MN)
  • Table 24 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Machine Learning (2021-2030) ($MN)
  • Table 25 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Querying Method (2021-2030) ($MN)
  • Table 26 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Speech Recognition (2021-2030) ($MN)
  • Table 27 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Application (2021-2030) ($MN)
  • Table 28 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Diabetes (2021-2030) ($MN)
  • Table 29 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Respiratory Issues (2021-2030) ($MN)
  • Table 30 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Weight Management & Fitness Monitoring (2021-2030) ($MN)
  • Table 31 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Cancer (2021-2030) ($MN)
  • Table 32 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Dehydration (2021-2030) ($MN)
  • Table 33 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Cardiovascular Diseases (2021-2030) ($MN)
  • Table 34 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Sleep Disorder (2021-2030) ($MN)
  • Table 35 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Viral Infection (2021-2030) ($MN)
  • Table 36 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Other Applications (2021-2030) ($MN)

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