Area of research
Artificial Intelligence · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Computer science, Artificial intelligence, Grading (engineering), Prostate cancer, Machine learning, and Prostate.
Foundation Model for Predicting Prognosis and Adjuvant Therapy Benefit From Digital Pathology in GI Cancers
Pancancer outcome prediction via a unified weakly supervised deep learning model
Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading
Deep Learning-Enabled Integration of Histology and Transcriptomics for Tissue Spatial Profile Analysis
CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting
The devil is in the details: a small-lesion sensitive weakly supervised learning framework for prostate cancer detection and grading
Automatic diagnosis and grading of Prostate Cancer with weakly supervised learning on whole slide images
A Real-Time QRS Detection Method Based on Phase Portraits and Box-Scoring Calculation