Researchers trained a machine learning tool on the BioMe EHR data bank and achieved a 94 percent sensitivity and 82 percent specificity rate for the tool.
The researchers told TCTMD that passively collected EHR data from health systems can be a huge resource for developing tools like their own.
“Prior to this work, machine-learning studies have been used to predict CAD on a case-control fashion as a binary disease,” meaning the disease is either present or absent, senior study author Ron Do, PhD, told TCTMD. “None of these studies have looked at using CAD on a spectrum of disease, despite prior studies showing that the disease exists on a spectrum.”
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