The global market for artificial intelligence (AI) in the medical devices industry is on track for a compound annual growth rate of 29.1% from US$336 million in 2023 to $1.2 billion in 2027, forecasts GlobalData, a UK-based data and analytics company.
Growth will be driven by the demand from healthcare systems to reduce time, costs and missed detections when diagnosing a growing number of patients with complex profiles, the company said.
"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," said Brian Hicks, senior analyst of medical devices at GlobalData.
"The consequence of this is that more patient profiles can be reviewed while also minimising any potential misdiagnoses."
The GlobalData report, "Artificial Intelligence [AI] in Healthcare – Thematic Research", notes that the underlying technology driving the trend is referred to as computer vision, and its diagnostic applications are being used by a wide range of specialists.
The ability of AI to reduce error rates in cancer detection has already been well demonstrated. One study published in a medical journal as far back as 2016 showed that pathologists who utilised AI in detecting cancer-positive lymph nodes had reduced their error rate from 3.4% to 0.5%.
"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," said Mr Hicks.
Various companies, including startups like Israel-based Aidoc, are specialising 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 going into the imaging and diagnostic fields. This is because more traditional hardware- and surgical instrument-focused medical technology companies have relatively limited opportunities to incorporate such technologies into their products.
"The importance of early detection of any [disease] indication cannot be understated," said Mr Hicks. "Thus, the ability for AI to improve and analyse difficult-to-detect tissue abnormalities, symptoms and complex patient profiles will enable earlier interventions and patient outcome."
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