https://www.sciencedaily.com/releases/2022/07/220714145147.htm

The goal of the team's study was to demonstrate the potential for deep-learning architecture to support early and reliable identification of cystic hygroma from first trimester ultrasound scans. Cystic hygroma is an embryonic condition that causes the lymphatic vascular system to develop abnormally. It's a rare and potentially life-threatening disorder that leads to fluid swelling around the head and neck.

The birth defect can typically be easily diagnosed prenatally during an ultrasound appointment, but Dr. Walker -- co-founder of the OMNI Research Group (Obstetrics, Maternal and Newborn Investigations) at The Ottawa Hospital -- and his research group wanted to test how well AI-driven pattern recognition could do the job.