Researchers led by Dr. Lev Barinov from Memorial Sloan Kettering Cancer Center in New York found that AI-based analysis of normal background parenchymal breast tissue on breast ultrasound could discriminate between the malignancy status of a lesion without having to observe it directly. In testing, the software outperformed the popular Tyrer-Cuzick risk-assessment model.

“These findings clearly demonstrate that AI holds the promise to make clinically meaningful delineations between high- and low-risk background breast tissue on breast ultrasound examination images,” Barinov told…