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AI-driven body-composition analysis predicts heart attack and stroke better than BMI

Conference
Radiological Society of North America annual meeting
Reuters Health -  07/12/2020 - Artificial intelligence (AI)-driven automated analysis of abdominal CT images outperforms traditional biomarkers for predicting risk of heart attack and stroke, new research indicates. "Established cardiovascular risk models rely on factors like weight and BMI that are crude surrogates of body composition," Dr. Kirti Magudia of the University of California, San Francisco, said in a news release. "It's well established that people with the same BMI can have markedly different proportions of muscle and fat. These differences are important for a variety of health outcomes," she added. A single axial CT slice of the abdomen shows the volume of subcutaneous fat area, visceral fat area and skeletal muscle area. However, manually measuring these individual areas is "time intensive and costly," Dr. Magudia noted in a presentation at the Radiological Society of North America (RSNA) annual meeting. Dr. Magudia was part of a multidi...


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