Area of research
Computational Theory and Mathematics · Artificial Intelligence
Research interest
Research interests include Computer science, Artificial intelligence, Medicine, Deep learning, Node (physics), and Embedding.
Delta-radiomics analysis based on magnetic resonance imaging to identify radiation proctitis in patients with cervical cancer after radiotherapy
MRI radiomics and nutritional-inflammatory biomarkers: a powerful combination for predicting progression-free survival in cervical cancer patients undergoing concurrent chemoradiotherapy
Learning user sentiment orientation in social networks for sentiment analysis
Hierarchical Representation Learning for Attributed Networks
Fast, scalable, and statistically robust cell extraction from large-scale neural calcium imaging datasets
A classified feature representation three-way decision model for sentiment analysis
Hierarchical Representation Learning for Attributed Networks
User’s Review Habits Enhanced Hierarchical Neural Network for Document-Level Sentiment Classification
Simultaneous left atrium anatomy and scar segmentations via deep learning in multiview information with attention
Multitask Learning for Estimating Multitype Cardiac Indices in MRI and CT Based on Adversarial Reverse Mapping
Deep Learning for Diagnosis of Chronic Myocardial Infarction on Nonenhanced Cardiac Cine MRI
Direct delineation of myocardial infarction without contrast agents using a joint motion feature learning architecture
Multi-granular mining for boundary regions in three-way decision theory