January 12, 2021 A diagnostic model that incorporates artificial intelligence (AI)-based quantitative analysis can significantly decrease false-positive rates for masses detected on screening breast ultrasound exams, potentially helping to reduce unnecessary biopsies, according to a study published online January 11 in
In a multicenter effort, researchers led by Dr. Soo-Yeon Kim, PhD, of Seoul National University Hospital in South Korea developed and tested a nomogram that encompasses radiologist assessments, as well as analysis of quantitative morphologic features extracted by a commercial deep learning-based computer-aided detection (CAD) software application.
They found that this diagnostic model could potentially cut the number of false positives from screening breast ultrasound by more than 40% without impacting sensitivity.
Seoul
Soult-ukpyolsi
South-korea
Soo-yeon-kim
Samsung-medison
Seoul-national-university-hospital
Samsung-medical-center
Severance-hospital
Seoul-national-university
Radiology
Radiologist
Medical-imaging