AI model estimates mortality risk on SPECT heart exams

Researchers at Cedars-Sinai Medical Center in Los Angeles developed a deep-learning model using SPECT myocardial perfusion imaging (MPI) and clinical data from more than 20,000 patients with coronary artery disease. The model performed well in making time-dependent risk predictions and shows promise as a tool for facilitating discussions of possible adverse events with patients, noted first author Dr. Konrad Pieszko, PhD, and colleagues.

“In [common practice], although a patient may be informed that they are at high risk for an adverse event, they are left with less information about…

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