Deep learning combines breast imaging data to predict cancer prognosis

Deep-learning models could have potential as predictive tools for breast cancer prognosis, a study published January 17 in Clinical Breast Cancer has found. A team led by Junqi Han, MD, from the Affiliated Hospital of Qingdao University in China found that its model combining data from mammography images, ultrasound images, and other characteristics performed well in predicting disease-free survival of breast cancer. “The combination of mammography and ultrasound images improved… performance for predicting breast cancer prognosis compared with single medical imaging modalities,” Han and colleagues wrote. AI and deep learning continue to be explored by radiologists for their potential to improve breast cancer diagnosis and prognosis. Han and colleagues focused on the latter for their study, attempting to establish and validate their deep learning methods that combine mammography, ultrasound, and clinical data to predict prognosis in breast cancer. The researchers included data from 1,242 patients recruited between 2013 and 2018 and divided them into training (n = 1,014) and testing groups (n = 228). They collected imaging data to establish deep-learning models using ResNet50. From there, the team used clinical data and imaging characteristics to select independent prognostic factors to establish a clinical model. In total, the team developed five models: ultrasound deep learning, mammography deep learning, ultrasound plus mammography deep learning, a clinical model,...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Breast Source Type: news