Area of research
Radiology, Nuclear Medicine and Imaging · Oncology
Research interest
Research interests include Radiomics and Machine Learning in Medical Imaging, Cancer Immunotherapy and Biomarkers, AI in cancer detection, and Ferroptosis and cancer prognosis.
Pancancer outcome prediction via a unified weakly supervised deep learning model
AI-based radiomic features predict outcomes and the added benefit of chemoimmunotherapy over chemotherapy in extensive stage small cell lung cancer: A multi-institutional study
Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer
Role of tumor infiltrating lymphocytes and spatial immune heterogeneity in sensitivity to PD-1 axis blockers in non-small cell lung cancer
Spatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict clinical benefit for immune checkpoint inhibitors
Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome