Artificial intelligence could refine CAD prognosis

By Eleanor McDermid A study shows that machine learning can predict mortality in patients with coronary artery disease (CAD) with greater accuracy than models based on coronary computed tomographic angiography (CCTA) or clinical variables. “Appreciating and integrating the myriad risk predictors in an individual patient is a challenge for the clinician”, say Piotr Slomka (Cedars-Sinai Medical Center, Los Angeles, California, USA) and co-researchers. They say the complexity increases along with the number of known risk factors, and “the potential influence of unexpected interactions between several weaker predictors in an individual patient is often overlooked.” But the team shows that machine learning, in which computers identify patterns in large and complex datasets, “is able to overcome these challenges, by providing deep integration of the comprehensive CCTA and clinical data.” Related Stories…


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