Artificial intelligence (AI) software developer Zebra Medical Vision and Israeli health system Clalit Health Services are directing attention to two research projects being presented at the upcoming RSNA 2018 meeting in Chicago.
The first study involves a retrospective cohort of 48,227 individuals with abdominal CT studies. Clalit researchers will report on Wednesday that a combination of automatic Zebra Medical algorithms was equivalent to the contemporary Fracture Risk Assessment Tool (FRAX) scoring system in providing risk stratification for major and hip-specific osteoporotic hip fractures, Zebra Medical said.
A second study to be presented on Tuesday morning showed that a coronary calcium score derived from nongated CT scans by Zebra Medical's algorithms led to 4.5% better risk classification for cardiac events, according to the company.
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)