Semi-Supervised Learning to Improve Generalizability of Cancer Associated-Venous Thromboembolism Risk Prediction Models
Clinical and Applied Thrombosis/Hemostasis
Published online on January 27, 2026
Abstract
Clinical and Applied Thrombosis/Hemostasis, Volume 32, January-December 2026.
ObjectiveThe purpose of this study is to develop and validate an improved CA-VTE risk prediction model based on semi-supervised learning (SSL) algorithm.MethodsThis study used a combined retrospective and prospective cohort design. First, data from 2100 ...
ObjectiveThe purpose of this study is to develop and validate an improved CA-VTE risk prediction model based on semi-supervised learning (SSL) algorithm.MethodsThis study used a combined retrospective and prospective cohort design. First, data from 2100 ...