{"paper_id":"a588e041-5741-4ed8-84cb-0a4d72663d45","body_text":"A Large Language Model For Clinical Outcomes Adjudication from Telephone Follow-up Interviews: A Secondary Analysis of a Multicenter Randomized Clinical Trial\nAuthors/Creators\n- 1. Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China\n- 2. Department of Radiology, Jinling Hospital, Nanjing Medical University, Nanjing, 210002, China\n- 3. AI lab, Deepwise Healthcare, Beijing, 100000, China\n- 4. Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, USA\n- 5. Department of Computer Science, The University of Hong Kong, Hong Kong, China\nDescription\nThe official source code and experimental setup for the paper \"A Large Language Model For Clinical Outcomes Adjudication from Telephone Follow-up Interviews: A Secondary Analysis of a Multicenter Randomized Clinical Trial\".\nThe repository includes all necessary scripts and configurations to reproduce the findings reported in the study.\nFor detailed instructions on setting up the environment and running the experiments, please see the README.md file.\nFiles\nOmniMedAI/FuLLM-v1.0.1.zip\nFiles\n(78.8 MB)\n| Name | Size | Download all |\n|---|---|---|\n|\nmd5:73be5ac447f8e5d7980336143a2a7d57\n|\n78.8 MB | Preview Download |\nAdditional details\nRelated works\n- Is supplement to\n- Software: https://github.com/OmniMedAI/FuLLM/tree/v1.0.1 (URL)\nSoftware\n- Repository URL\n- https://github.com/OmniMedAI/FuLLM","source_license":"CC0","license_restricted":false}