An Yan

GWDRO-Lung: Gromov–Wasserstein distributionally robust learning for calibrated pulmonary nodule malignancy prediction across imaging cohorts

Low-dose chest computed tomography (CT) screening detects pulmonary nodules whose malignancy risk must be triaged, yet deep-learning risk models often lose both accuracy and calibration when transferred to a different scanner, protocol, or population. We developed GWDRO-Lung, a c...