https://www.thebusinessresearchcompany.com/report/artificial-intelligence-in-medicine-global-market-report
According to The Business Research Company’s Artificial Intelligence In Medicine Global Market Report 2024, The artificial intelligence in medicine market size has grown exponentially in recent years. It will grow from $8.01 billion in 2023 to $11.19 billion in 2024 at a compound annual growth rate (CAGR) of 39.8%. The growth in the historic period can be attributed to increased emphasis on ensuring patient well-being and relative shortage of physicians, increase of skilled healthcare professionals, increase in the processing power of ai systems .
The artificial intelligence in medicine market size is expected to see exponential growth in the next few years. It will grow to $42.11 billion in 2028 at a compound annual growth rate (CAGR) of 39.3%. The growth in the forecast period can be attributed to rising prevalence of chronic diseases, growing emphasis on the adoption of digital transformation practices. Major trends in the forecast period include development of medical robots, introducing patient management application to witness significant growth, ai in drug discovery and advance precision medicine .
The increasing interest in real-time remote patient monitoring (RPM) systems is expected to propel the growth of artificial intelligence in the medicine market going forward. A remote patient monitoring system is a technology-driven healthcare solution designed to monitor patients’ health outside of traditional healthcare settings. Artificial intelligence (AI) in medicine has significantly transformed remote patient monitoring by leveraging advanced algorithms to analyze extensive patient data, offering predictive insights and enabling personalized care. For instance, in August 2023, according to a survey conducted by Vivalink, a US-based digital healthcare company, there was a significant increase in the use of remote patient monitoring (RPM) by clinicians, rising from 20% in 2021 to 81% currently, marking an increase of 305%. Therefore, the increasing interest in real-time remote patient monitoring (RPM) systems is driving the growth of artificial intelligence in the medicine market.
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The artificial intelligence in medicine market market covered in this report is segmented –
1) By Type: Hardware, Software, Services
2) By Technology: Machine Learning, Natural Language Processing, Context-Aware Processing, Computer Vision
3) By Application : Medical Administration And Support, Patient Management, Research And Development, Other Applications
4) By End User: Hospitals, Clinics, Research Institutions
Major companies operating in the artificial intelligence in the medicine market are focused on developing innovative solutions, such as AI-powered platforms, to provide reliable services to customers. An AI-powered platform is a software solution incorporating artificial intelligence (AI) technologies to automate tasks, analyze data, and make predictions. For instance, in April 2023, OM1 Inc., a US-based digital health company, launched PhenOM. It uses real-world data and advanced analytics to identify unique digital phenotypes associated with conditions and outcomes, creating fingerprints for different patient groups. PhenOM can analyze individual patient data to predict risks, highlight opportunities for intervention, and inform treatment decisions.
The artificial intelligence in medicine market report table of contents includes:
1. Executive Summary
2. Artificial Intelligence In Medicine Market Characteristics
3. Artificial Intelligence In Medicine Market Trends And Strategies
4. Artificial Intelligence In Medicine Market – Macro Economic Scenario
5. Global Artificial Intelligence In Medicine Market Size and Growth
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32. Global Artificial Intelligence In Medicine Market Competitive Benchmarking
33. Global Artificial Intelligence In Medicine Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Artificial Intelligence In Medicine Market
35. Artificial Intelligence In Medicine Market Future Outlook and Potential Analysis
36. Appendix
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