Selbyville, Delaware, Oct. 07, 2024 (GLOBE NEWSWIRE) --
Artificial Intelligence in Diagnostics Market size was valued at USD 1.1 billion in 2023. Projections indicate a robust development trajectory, with an expected CAGR of 22.2% from 2024 to 2032, due to the rising prevalence of chronic diseases and the growing demand for AI tools in disease diagnosis.
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As chronic diseases become more prevalent, healthcare providers increasingly turn to AI solutions. These tools enhance early detection, ensure precise diagnoses, and facilitate tailored treatment strategies for conditions like diabetes and cancer. Factors such as an aging population, sedentary lifestyles, and poor dietary habits have fueled the rise in chronic conditions. This has led to a significant increase in the target population and heightened healthcare demand. The World Health Organization (WHO) reported in 2023 that chronic diseases are responsible for 71% of global deaths, with cardiovascular diseases alone accounting for 17.9 million fatalities annually.
The demand for AI tools is further propelling the progression of the artificial intelligence in diagnostics market. Healthcare facilities prioritize enhanced diagnostic precision, operational efficiency, and improved patient outcomes. This demand stems from the growing complexity of medical data, the need for faster and more reliable diagnostic processes, and an intensified focus on personalized medicine. Moreover, swift advancements in AI technologies and the widespread adoption of digital healthcare platforms are hastening the integration of AI tools across various diagnostic applications.
The overall AI in diagnostic industry is segmented based on component, application, end-use, and region.
In 2023, the radiology segment led the artificial intelligence in diagnostics market with a revenue share of 28.4%. Radiology, which encompasses the analysis of vast amounts of medical images like X-rays, CT scans, MRIs, and ultrasounds, has found a prime ally in AI tools. These tools excel in handling and interpreting medical images, significantly boosting diagnostic efficiency. Radiology was among the first medical domains to embrace AI, especially in image recognition and interpretation. This early adoption has resulted in mature and refined AI tools, now widely trusted across healthcare facilities.
The artificial intelligence in diagnostics market from hospitals & clinics segment is projected to reach USD 3.3 billion by 2032. Given their vast and diverse patient base, hospitals and clinics require a broad spectrum of diagnostic services. AI-powered diagnostic tools play a pivotal role in managing the high volume of procedures, from imaging to lab tests, ensuring swift and accurate results. Being at the forefront of adopting advanced medical technologies, hospitals and clinics leverage their resources and infrastructure to seamlessly integrate AI systems across departments, enhancing diagnostic capabilities and elevating patient care.
In 2023, North America artificial intelligence in diagnostics market accounted for USD 451.6 million, with projections indicating a CAGR of 21.2% from 2024 to 2032. The U.S. stands out as a leader in embracing state-of-the-art healthcare technologies. Healthcare providers in the region are eager to adopt AI-driven diagnostic tools, aiming to boost accuracy, minimize errors, and enhance patient outcomes. This trend is bolstered by a robust emphasis on technological innovation and a solid healthcare infrastructure. Furthermore, with a high prevalence of chronic diseases like cardiovascular issues, diabetes, and cancer, the region recognizes the pivotal role of AI-based diagnostics in early detection and management, further fueling the demand for AI solutions in healthcare.
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Major players in artificial intelligence in diagnostics market include Aidoc, AliveCor Inc., Digital Diagnostics, Inc., Enlitic, IBM Corporation, Imagen Technologies, NVIDIA Corporation, PathAI, RADLogics, Riverain Technologies, Siemens Healthineers, Sophia Genetics, Tempus, Vuno, Inc., and Zebra Medical Vision, Inc. among others.
Partial Table of Contents (ToC) of the report:
Chapter 1 Methodology & Scope
1.1 Market scope & definitions
1.2 Research design
1.2.1 Research approach
1.2.2 Data collection methods
1.3 Base estimates & 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 3600 synopsis
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.2 Industry impact forces
3.2.1 Growth drivers
3.2.1.1 Rising prevalence of chronic diseases
3.2.1.2 Increasing demand for AI tools
3.2.1.3 Technological advancements
3.2.1.4 Favorable government initiatives and funding
3.2.2 Industry pitfalls & challenges
3.2.2.1 High procurement and maintenance costs
3.2.2.2 Data privacy and security concerns
3.3 Growth potential analysis
3.4 Regulatory landscape
3.5 Technology landscape
3.6 Start-up scenario
3.7 Porter's analysis
3.8 PESTEL analysis
3.9 Future market trends
3.10 Gap analysis
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