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Premium Report Details
Base Year: 2023
Companies covered: 15
Tables & Figures: 119
Countries covered: 23
Pages: 100
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Artificial Intelligence in Diagnostics Market
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AI in Diagnostics Market Size
Artificial Intelligence in diagnostics market size was valued at USD 1.1 billion in 2023 and is expected to exhibit growth at a CAGR of 22.2% from 2024 to 2032. The rising market growth can be attributed to increasing prevalence of chronic diseases coupled with growing demand for AI tools in disease diagnosis.
The rising prevalence of chronic diseases is a key factor propelling the market growth as healthcare providers increasingly leverage AI solutions to improve early detection, precise diagnosis, and tailored treatment strategies for conditions such as diabetes and cancer among others. The surge in chronic conditions is fueled by various factors including aging population, sedentary lifestyles, and suboptimal dietary habits, which resulted in significant increase in target population and healthcare demand. For instance, the World Health Organization (WHO) reported in 2023 that chronic diseases account for 71% of all deaths globally, with cardiovascular diseases alone responsible for 17.9 million deaths annually.
Additionally, the rising demand for AI tools is catalyzing the growth of the AI in diagnostics market, as healthcare facilities increasingly focus on enhanced diagnostic precision, operational efficiency, and superior patient outcomes. This demand is driven by the increasing complexity of medical data, the need for faster and more reliable diagnostic processes, and the growing emphasis on personalized medicine. Furthermore, rapid advancements in AI technologies and the broader adoption of digital healthcare platforms are accelerating the integration of AI tools across diagnostic applications.
Artificial intelligence in diagnostics refers to the application of advanced AI technologies to analyze medical data and assist in the diagnosis of diseases and medical conditions. This involves the use of algorithms and models that can process large volumes of patient data, including medical images, lab results, and electronic health records, to identify patterns, predict outcomes, and provide diagnostic insights.