{
  "id": 9395,
  "url": "https://doi.org/10.1038/s41746-023-00958-w",
  "title": "A study of generative large language model for medical research and healthcare",
  "summary": "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 gene",
  "authors": "Peng Cheng, Xi Yang, Aokun Chen, Kaleb E. Smith, Nima PourNejatian, Anthony Costa",
  "category": "research",
  "topics": "healthcare",
  "orgs": "openai",
  "regions": null,
  "published_at": "2023-11-16T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:54.153Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/9395",
  "original_url": "https://doi.org/10.1038/s41746-023-00958-w",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}