A study of generative large language model for medical research and healthcare

There are enormous enthusiasm and concerns in applying large language models (LLMs) to healthcare. Yet current assumptions are based on general-purpose LLMs such as ChatGPT, which are not developed for medical use. This study develops a generative clinical LLM, GatorTronGPT, using 277 billion words of text including (1) 82 billion words of clinical text from 126 clinical departments and approximately 2 million patients at the University of Florida Health and (2) 195 billion words of diverse general English text. We train GatorTronGPT using a GPT-3 architecture with up to 20 billion parameters and evaluate its utility for biomedical natural language processing (NLP) and healthcare text generation. GatorTronGPT…

• PO
  Patient-Centered Outcomes Research Institute

  Award: ME-2018C3-14754
• UO
  University of Florida Health
• CA
  Clinical and Translational Science Institute, University of Florida
• NI
  National Institute on Aging

  Awards: R56AG069880, NIA R56AG069880
• NC
  National Cancer Institute

  Awards: R56AG069880, 1R01CA246418