AI abdominal fat measure predicts heart attack and stroke
https://www.sciencedaily.com/releases/2020/12/201202114507.htm
"Established cardiovascular risk models rely on factors like weight and BMI that are crude surrogates of body composition," said Kirti Magudia, M.D., Ph.D., an abdominal imaging and ultrasound fellow at the University of California San Francisco. "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."
Unlike BMI, which is based on height and weight, a single axial CT slice of the abdomen visualizes the volume of subcutaneous fat area, visceral fat area and skeletal muscle area. However, manually measuring these individual areas is time intensive and costly.