Shan Chen

Jan 8, 2025 | nature.com | Jack Gallifant |Saleem Ameen |Yindalon Aphinyanaphongs |Shan Chen |Giovanni E. Cacciamani |Roxana Daneshjou | +7 more

AbstractLarge language models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present transparent reporting of a multivariable model for individual prognosis or diagnosis (TRIPOD)-LLM, an extension of the TRIPOD + artificial intelligence statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion.

Mar 27, 2024 | medrxiv.org | Wonjin Yoon |Shan Chen |Yanjun Gao |Dmitriy Dligach

The authors have declared no competing interest. Research reported in this publication was supported by the National Library Of Medicine of the National Institutes of Health under Award Number R01LM012973, and by the National Institute Of Mental Health of the National Institutes of Health under Award Number R01MH126977. I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Jan 10, 2024 | nature.com | Shan Chen |Benjamin H. Kann

AbstractSocial determinants of health (SDoH) play a critical role in patient outcomes, yet their documentation is often missing or incomplete in the structured data of electronic health records (EHRs). Large language models (LLMs) could enable high-throughput extraction of SDoH from the EHR to support research and clinical care. However, class imbalance and data limitations present challenges for this sparsely documented yet critical information.

Aug 24, 2023 | jamanetwork.com | Shan Chen |Mass General Brigham |Benjamin H. Kann |Michael Foote

Large language models (LLMs) underlying chatbots1 can mimic human language and quickly return detailed and coherent-seeming responses. These properties can obscure that chatbots might provide inaccurate information. Because patients often use the internet for self-education,2 some will undoubtedly use LLM chatbots to find cancer-related medical information, which could be associated with the generation and amplification of misinformation.