For the study, researchers analyzed 14 studies published between 2012 and 2019. The studies compared the diagnostic performance of AI models to healthcare professionals based on a review of medical images.
On average, AI algorithms offered correct diagnoses 86.4 percent of the time, compared to 87 percent for clinicians. AI models also accurately identified patients who did not have the disease 92.5 percent of the time. This rate was 90.5 percent for clinicians.
Despite this finding, researchers noted many studies comparing diagnostic ability contain methodological deficiencies and poor reporting.
“These issues are pertinent for ensuring studies of deep learning diagnostics … are of sufficient quality to evaluate the performance of these algorithms in a way that can benefit patients and health systems in clinical practice,” the study authors concluded.
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