Journal of Medical Internet Research

Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study

The stacking model achieved ROC-AUCs of 0.995, 0.838, and 0.721 in the training, internal validation, and external validation sets, respectively. Key predictors—total bilirubin, lactate, prothrombin ...
IEEE

CIDTL: A Cross-In Domain Transfer Learning Model for Vehicular Trajectory Prediction Under Few-Shot Conditions of Aggressive Driving Behavior

Abstract: Data-driven methods have demonstrated high trajectory prediction accuracy with advancements in trajectory monitoring technology and deep learning algorithms. Human driving behavior shows ...
IEEE

Mining Cross-Modality Implicit Semantic Association for Unsupervised Visible-Infrared Person Re-Identification

Abstract: Unsupervised visible-infrared person reidentification (US-VI-ReID) seeks to learn a cross-modality retrieval model without relying on manual annotations, thereby reducing the high cost ...