The global market for artificial intelligence in the medical devices industry is set to grow at a compound annual growth rate (CAGR) of 29.1% from $336 million in 2023 to $1.2 billion in 2027, driven by the demand for healthcare systems to reduce time, costs, and missed detections when diagnosing a growing number of patients with complex profiles, forecasts GlobalData, a leading data and analytics company.
Brian Hicks, Senior Analyst of Medical Devices at GlobalData, comments: “A common use of AI in medical has been in diagnostic settings, where the speed and accuracy of diagnosing difficult-to-identify image abnormalities by the human eye are flagged by AI algorithms. The consequence of this is that more patient profiles can be reviewed while also minimizing any potential misdiagnoses.”
GlobalData’s “Artificial Intelligence (AI) in Healthcare – Thematic Research” report reveals that the underlying technology that drives this trend is referred to as computer vision, and its diagnostic applications are leveraged by wide-ranging specialists.
The use of AI in decreasing error rates of cancer detection has already well demonstrated, where one study as far back as 2016 by Wang and colleagues showed that pathologists who had utilized AI in detecting cancer-positive lymph nodes had reduced their error rate from 3.4% to 0.5%.
Hicks adds: “Furthermore, due to the ability of AI to flag potential indication-positive cases in a fraction of the time it takes for physicians, with similar if not greater accuracy, many additional patient profiles can be reviewed with unprecedented speed.”
Various companies, including startups like Aidoc are specializing in medical imaging using AI and its associated deep learning technology. GlobalData research reveals that most of the AI-related investments in the medical industry are poured into those within the imaging and diagnostic spaces, as more traditional hardware and surgical instrument-focused MedTech companies have relatively limited opportunities to incorporate such technologies into their products.
Hicks concludes: “The importance of early detection of any indication cannot be understated; thus, the ability for AI to improve and analyze difficult-to-detect tissue abnormalities, symptoms, and complex patient profiles will enable earlier interventions and patient outcome.”
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