Israeli artificial intelligence (AI) software developer Aidoc has released new AI software for identifying strokes on head CT scans and helping to triage patients.
The software package includes deep learning-based modules for the automatic detection of stroke on CT scans. The software sends cases deemed urgent to the top of the radiologist worklist and reveals whether the stroke was a result of acute intracranial hemorrhage (hemorrhagic) or large-vessel occlusion (ischemic), reducing the amount of time patients need to wait before receiving appropriate surgical treatment, Aidoc said.
Aidoc's large-vessel occlusion AI module has already received the CE Mark, and its intracranial hemorrhage module received the CE Mark and U.S. Food and Drug Administration (FDA) clearance last year.
![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)
