Area of research
Artificial Intelligence · Molecular Biology
Research interest
Research interests include Topic Modeling, Natural Language Processing Techniques, Biomedical Text Mining and Ontologies, and Artificial Intelligence in Healthcare and Education.
Multimodal AI generates virtual population for tumor microenvironment modeling
Exploring the Future of AI in Clinical Collaboration: A Study on Tumor Board Case Preparation
A Multimodal Biomedical Foundation Model Trained from Fifteen Million Image–Text Pairs
A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities.
A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings
A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings.
TRIALSCOPE — A Framework for Clinical Trial Simulation from Real-World Data
A whole-slide foundation model for digital pathology from real-world data.
Multimodal Foundation Models for Medical Imaging - A Systematic Review and Implementation Guidelines
Widespread Adoption of Precision Anticancer Therapies After Implementation of Pathologist-Directed Comprehensive Genomic Profiling Across a Large US Health System.
Widespread adoption of precision anticancer therapies after implementation of pathologist-directed comprehensive genomic profiling across a large US health system
Fine-tuning large neural language models for biomedical natural language processing
Precision Health in the Age of Large Language Models
BioGPT: generative pre-trained transformer for biomedical text generation and mining.
Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing
The Deep Inspiration Breath-Hold Technique May Be a Win-Win Option for the Treatment of Patients in Node-Positive Early Left-Sided Breast Cancer.
Cross-Sentence <i>N</i>-ary Relation Extraction with Graph LSTMs
Classification of common human diseases derived from shared genetic and environmental determinants
Molecularly targeted drug combinations demonstrate selective effectiveness for myeloid- and lymphoid-derived hematologic malignancies