Search Submissions 🔎

A Recent Evaluation on the Performance of Llms on Radiation Oncology Physics Using Questions of Randomly Shuffled Options

Authors: Dequan Chen, Jason Michael Holmes, Tianming Liu, Wei Liu, Zhengliang Liu, Jiajian Shen, Peilong Wang

Affiliation: Department of Radiology, Mayo Clinic, Department of Radiation Oncology, Mayo Clinic, School of Computing, University of Georgia

Abstract Preview: Purpose:
We present a study to evaluate the performance of large language models (LLMs) in answering radiation oncology physics questions, focusing on the recently released models.
Methods:
A...

Reasoning-Driven Prompts Improve EHR-Based Outcome Prediction and Clinical Interpretability in Large Language Models

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...