Area of research
Radiology, Nuclear Medicine and Imaging · Artificial Intelligence
Research interest
Research interests include COVID-19 diagnosis using AI, Radiomics and Machine Learning in Medical Imaging, Machine Learning in Healthcare, and Retinal Imaging and Analysis.
Explainable differential diagnosis with dual-inference large language models
Uncertainty-aware large language models for explainable disease diagnosis
A survey of recent methods for addressing AI fairness and bias in biomedicine
Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge
Deep learning with noisy labels in medical prediction problems: a scoping review
Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modeling
A scoping review on multimodal deep learning in biomedical images and texts
Improving model fairness in image-based computer-aided diagnosis
Automated diagnosing primary open-angle glaucoma from fundus image by simulating human’s grading with deep learning
Fully automated segmentation of brain tumor from multiparametric MRI using 3D context deep supervised U‐Net
Artificial intelligence in tumor subregion analysis based on medical imaging: A review