Area of research
Radiology, Nuclear Medicine and Imaging · Artificial Intelligence
Research interest
Research interests include Radiomics and Machine Learning in Medical Imaging, AI in cancer detection, COVID-19 diagnosis using AI, and Colorectal Cancer Screening and Detection.
Multi-modal large language models in radiology: principles, applications, and potential
Advancements in early detection of pancreatic cancer: the role of artificial intelligence and novel imaging techniques
ChatGPT and Other Large Language Models Are Double-edged Swords
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning
Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms
Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening
Distribution, source, and environmental risk assessment of phthalate esters (PAEs) in water, suspended particulate matter, and sediment of a typical Yangtze River Delta City, China
Globally-Aware Multiple Instance Classifier for Breast Cancer Screening
Breast Density Classification with Deep Convolutional Neural Networks