mlHealth 360 has received U.S. Food and Drug Administration (FDA) 510(k) clearance for its Scaida BrainCT-ICH AI-powered triage software.
The British Columbia-based firm said its Canadian-developed AI is intended to assist trained radiologists in workflow triage by flagging suspected intracranial hemorrhages (ICH). The system automatically analyzes noncontrast head CT scans, but it is not intended for primary diagnostic interpretation, the company noted.
In its announcement, mlHealth 360 said the software successfully prioritizes critical cases with a specificity of 89%, sensitivity of 87%, area under the curve (AUC) of 0.926, and average processing time of 5.97 seconds.
The firm added that the FDA clearance is supported by "rigorous" validation across six U.S. institutions, covering multiple scanner manufacturers and diverse patient populations.
![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)
