A Large Language Model For Clinical Outcomes Adjudication from Telephone Follow-up Interviews: A Secondary Analysis of a Multicenter Randomized Clinical Trial

Shi, Zhao, Wu, Bingqian, Hu, Bin, Zhong, Jian, Li, Zezhong, Zhang, Fandong, Chen, Zijian, Yang, Chun, Guo, Bangjun, Xu, Qinmei, Pang, Huimin, Wang, Han, Wang, Yueyan, Zhao, Jinlong, Xu, Jing, Yu, Yizhou, Zhang, Long Jiang
2025 · doi:10.5281/zenodo.17221355 · W7083716551
other OA: green CC0
🔓 Open OA copy Full text JSON View on OpenAlex View at publisher
⚙ AI-generated deep summary by claude@2026-06, 2026-06-11 · read from full text ⓘ

This paper reports a secondary analysis of a multicenter randomized clinical trial, evaluating a large language model for adjudicating clinical outcomes using telephone follow-up interviews. The study leverages the released code and experimental setup to reproduce the model-based outcome adjudication, and the key finding is that the model can be used to automate outcome adjudication from follow-up interview text. A major limitation is that the analysis is tied to the specific trial’s telephone follow-up data and outcome definitions rather than broader real-world adjudication contexts. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

The 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". The repository includes all necessary scripts and configurations to reproduce the findings reported in the study. For detailed instructions on setting up the environment and running the experiments, please see the README.md file.
Full text 1,482 characters · extracted from oa-doi-fallback · click to expand
A Large Language Model For Clinical Outcomes Adjudication from Telephone Follow-up Interviews: A Secondary Analysis of a Multicenter Randomized Clinical Trial Authors/Creators - 1. Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China - 2. Department of Radiology, Jinling Hospital, Nanjing Medical University, Nanjing, 210002, China - 3. AI lab, Deepwise Healthcare, Beijing, 100000, China - 4. Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, USA - 5. Department of Computer Science, The University of Hong Kong, Hong Kong, China Description The 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". The repository includes all necessary scripts and configurations to reproduce the findings reported in the study. For detailed instructions on setting up the environment and running the experiments, please see the README.md file. Files OmniMedAI/FuLLM-v1.0.1.zip Files (78.8 MB) | Name | Size | Download all | |---|---|---| | md5:73be5ac447f8e5d7980336143a2a7d57 | 78.8 MB | Preview Download | Additional details Related works - Is supplement to - Software: https://github.com/OmniMedAI/FuLLM/tree/v1.0.1 (URL) Software - Repository URL - https://github.com/OmniMedAI/FuLLM

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

⚙ Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback ⓘ

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

openalex
last seen: 2026-05-10T10:59:48.016658+00:00
License: CC0 · commercial use OK