Authors: Steve Braunstein, Yannet Interian, Hui Lin, Bo Liu, Janine Lupo, Olivier Morin, Benedict Neo
Affiliation: Radiation Oncology, University of California San Francisco, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, University of California San Francisco, Department of Data Science, University of San Francisco, University of San Francisco
Abstract Preview: Purpose: Large Language Models (LLMs) demonstrate strong general text comprehension but remain limited in oncology due to insufficient contextual alignment. We pilot embedding alignment through radiol...
Authors: Shreyas Anil, Jason Chan, Arushi Gulati, Yannet Interian, Hui Lin, Benedict Neo, Andrea Park, Bhumika Srinivas
Affiliation: Department of Otolaryngology Head and Neck Surgery, University of California San Francisco, Department of Data Science, University of San Francisco, Department of Radiation Oncology, University of California San Francisco
Abstract Preview: Purpose: Hospital readmission prediction models often rely on structured Electronic Health Record (EHR) data, overlooking critical insights from unstructured clinical notes. This study presents a mult...
Authors: Shreyas Anil, Jason Chan, Arushi Gulati, Yannet Interian, Hui Lin, Benedict Neo, Andrea Park, Bhumika Srinivas
Affiliation: Department of Otolaryngology Head and Neck Surgery, University of California San Francisco, Department of Data Science, University of San Francisco, Department of Radiation Oncology, University of California San Francisco, University of San Francisco
Abstract Preview: Purpose: As Large Language Models (LLMs) continue to evolve, their ability to analyze Electronic Health Record (EHR) notes for clinical decision support expands. Chain of Thought (COT) reasoning, an e...