Using machine learning, noninvasive test can assess CAD in 3 minutes

Artificial intelligence

A machine learning algorithm derived from thoracic phase signals can identify obstructive coronary artery disease (CAD) with the same accuracy as existing functional tests, according to a study published Aug. 8 in PLOS One. The signals can be collected in about three minutes and don’t require the patient to exercise or be exposed to radiation, contrast media or pharmacological stress.