Our projects span diseases and data modalities, incorporating machine learning for computational phenotyping. Our main efforts focus in medical image analysis, clinical NLP, and mHealth. Our NIH funding includes projects in prostate cancer, thyroid cancer, acute stroke, and heart failure.
We have developed an electronic health record (EHR) platform for improving diagnostic accuracy and efficiency through the integration of clinical data with AI support. The platform is integrated with UCLA’s Epic EHR for cancer diagnosis, with over 10,000 cases completed.
Our lab maintains several project resources. For compute, we have two NVIDIA DGX-1 GPU processing servers that have high-speed connections to our 500TB data server. We also maintain a Leica/Aperio GT450 whole slide scanner for digitizing histology slides.