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AI bolsters specificity of screening breast ultrasound


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. ....

Soult Ukpyolsi , South Korea , Soo Yeon Kim , Samsung Medison , Seoul National University Hospital , Samsung Medical Center , Severance Hospital , Seoul National University , Medical Imaging , Artificial Intelligence , Deep Learning , Breast Ultrasound , Breast Masses , தெற்கு கொரியா , சூ யோன் கிம் , சாம்சங் இடைநிலை , சியோல் தேசிய பல்கலைக்கழகம் மருத்துவமனை , சாம்சங் மருத்துவ மையம் , பிரித்தல் மருத்துவமனை , சியோல் தேசிய பல்கலைக்கழகம் , மருத்துவ இமேஜிங் , செயற்கை உளவுத்துறை , ஆழமான கற்றல் , மார்பக அல்ட்ராசவுண்ட் , மார்பக வெகுஜன ,