{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T15:44:21Z","timestamp":1764171861227,"version":"3.46.0"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T00:00:00Z","timestamp":1764115200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T00:00:00Z","timestamp":1764115200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Brain impact foundation"},{"DOI":"10.13039\/501100003710","name":"Korea Health Industry Development Institute","doi-asserted-by":"publisher","award":["HI21C1074"],"award-info":[{"award-number":["HI21C1074"]}],"id":[{"id":"10.13039\/501100003710","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"DOI":"10.1186\/s12911-025-03239-6","type":"journal-article","created":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T15:36:47Z","timestamp":1764171407000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A prompt framework for enhancing LLM-based explainability of medical machine learning models: an intensive care unit application"],"prefix":"10.1186","volume":"25","author":[{"given":"Sujung","family":"Lee","sequence":"first","affiliation":[]},{"given":"Won Ik","family":"Cho","sequence":"additional","affiliation":[]},{"given":"Youngrong","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Duck Ju","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Kyeng Hyun","family":"Nam","sequence":"additional","affiliation":[]},{"given":"Sangmin","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Jungyo","family":"Suh","sequence":"additional","affiliation":[]},{"given":"Taehoon","family":"Ko","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,26]]},"reference":[{"issue":"7956","key":"3239_CR1","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1038\/s41586-023-05881-4","volume":"616","author":"M Moor","year":"2023","unstructured":"Moor M, et al. Foundation models for generalist medical artificial intelligence. Nature. 2023;616(7956):259\u201365.","journal-title":"Nature"},{"key":"3239_CR2","doi-asserted-by":"crossref","unstructured":"Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med (2019): 1347\u201358.","DOI":"10.1056\/NEJMra1814259"},{"issue":"5","key":"3239_CR3","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","volume":"1","author":"C Rudin","year":"2019","unstructured":"Rudin C. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nat Mach Intell. 2019;1(5):206\u201315.","journal-title":"Nat Mach Intell"},{"key":"3239_CR4","doi-asserted-by":"crossref","unstructured":"Adadi A. and Mohammed Berrada. Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE access 6 (2018): 52138\u201360.","DOI":"10.1109\/ACCESS.2018.2870052"},{"key":"3239_CR5","doi-asserted-by":"crossref","unstructured":"Farah L et al. Assessment of performance, interpretability, and explainability in artificial intelligence\u2013based health technologies: what healthcare stakeholders need to know. Mayo Clinic Proceedings: Digital Health 1.2 (2023): 120\u2013138.","DOI":"10.1016\/j.mcpdig.2023.02.004"},{"key":"3239_CR6","unstructured":"Lundberg SM, Su-In. Lee. A unified approach to interpreting model predictions. Adv Neural Inf Process Syst 30 (2017)."},{"key":"3239_CR7","unstructured":"Tonekaboni S et al. What clinicians want: contextualizing explainable machine learning for clinical end use. Machine learning for healthcare conference. PMLR, 2019."},{"issue":"1","key":"3239_CR8","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1186\/s12910-022-00842-4","volume":"23","author":"N Hallowell","year":"2022","unstructured":"Hallowell N, et al. I don\u2019t think people are ready to trust these algorithms at face value: trust and the use of machine learning algorithms in the diagnosis of rare disease. BMC Med Ethics. 2022;23(1):112.","journal-title":"BMC Med Ethics"},{"issue":"4","key":"3239_CR9","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1093\/jamia\/ocz229","volume":"27","author":"WK Diprose","year":"2020","unstructured":"Diprose WK, et al. Physician understanding, explainability, and trust in a hypothetical machine learning risk calculator. J Am Med Inform Assoc. 2020;27(4):592\u2013600.","journal-title":"J Am Med Inform Assoc"},{"key":"3239_CR10","doi-asserted-by":"crossref","unstructured":"Mohamed Y, Abas et al. Decoding the black box: explainable AI (XAI) for cancer diagnosis, prognosis, and treatment planning-A state-of-the Art systematic review. Int J Med Informatics (2024): 105689.","DOI":"10.1016\/j.ijmedinf.2024.105689"},{"key":"3239_CR11","doi-asserted-by":"publisher","first-page":"e53207","DOI":"10.2196\/53207","volume":"3","author":"R Rosenbacke","year":"2024","unstructured":"Rosenbacke R, et al. How explainable artificial intelligence can increase or decrease clinicians\u2019 trust in AI applications in health care. Syst Rev JMIR AI. 2024;3:e53207.","journal-title":"Syst Rev JMIR AI"},{"key":"3239_CR12","doi-asserted-by":"crossref","unstructured":"Menon AV et al. Lessons from Clinical Communications for Explainable AI. Proceedings of the AAAI\/ACM Conference on AI, Ethics, and Society. Vol. 7. 2024.","DOI":"10.1609\/aies.v7i1.31695"},{"key":"3239_CR13","unstructured":"OpenAI. (2023). GPT-4 Technical Report. arXiv preprint arXiv:2303.08774."},{"key":"3239_CR14","doi-asserted-by":"publisher","unstructured":"Lee S, Cho WI, Park C, Ko T. Well-Tempered Medical Prompt Engineering for Explainable Extubation. Studies in health technology and informatics, 2024;316:587\u2013588. https:\/\/doi.org\/10.3233\/SHTI240482","DOI":"10.3233\/SHTI240482"},{"issue":"8","key":"3239_CR15","doi-asserted-by":"publisher","first-page":"1930","DOI":"10.1038\/s41591-023-02448-8","volume":"29","author":"AJ Thirunavukarasu","year":"2023","unstructured":"Thirunavukarasu AJ, Ting DSJ, Elangovan K, Gutierrez L, Tan TF, Ting DS W. Large Language models in medicine including generative pretrained transformer 4 (GPT-4). Nat Med. 2023;29(8):1930\u201340.","journal-title":"Nat Med"},{"issue":"1","key":"3239_CR16","doi-asserted-by":"publisher","first-page":"160035","DOI":"10.1038\/sdata.2016.35","volume":"3","author":"AEW Johnson","year":"2016","unstructured":"Johnson AEW, Pollard TJ, Shen L, et al. MIMIC-III, a freely accessible critical care database. Sci Data. 2016;3(1):160035. https:\/\/doi.org\/10.1038\/sdata.2016.35.","journal-title":"Sci Data"},{"key":"3239_CR17","doi-asserted-by":"publisher","first-page":"103340","DOI":"10.1016\/j.iccn.2022.103340","volume":"74","author":"W Li","year":"2023","unstructured":"Li W, Zhang Y, Wang Z, Jia D, Zhang C, Ma X, Zhang Z. The risk factors of reintubation in intensive care unit patients on mechanical ventilation: A systematic review and meta-analysis. Intensive Crit Care Nurs. 2023;74:103340.","journal-title":"Intensive Crit Care Nurs"},{"key":"3239_CR18","doi-asserted-by":"crossref","unstructured":"Li H et al. Exposing numeracy gaps: A benchmark to evaluate fundamental numerical abilities in large language models. arXiv preprint arXiv:2502.11075 (2025).","DOI":"10.18653\/v1\/2025.findings-acl.1026"},{"issue":"2","key":"3239_CR19","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s00296-023-05464-6","volume":"44","author":"M Krusche","year":"2024","unstructured":"Krusche M, et al. Diagnostic accuracy of a large Language model in rheumatology: comparison of physician and ChatGPT-4. Rheumatol Int. 2024;44(2):303\u20136.","journal-title":"Rheumatol Int"},{"key":"3239_CR20","doi-asserted-by":"crossref","unstructured":"Meng X et al. The application of large language models in medicine: A scoping review. Iscience 2024;27:5.","DOI":"10.1016\/j.isci.2024.109713"},{"key":"3239_CR21","unstructured":"Zeng X. Enhancing the Interpretability of SHAP Values Using Large Language Models. arXiv preprint arXiv:2409.00079 (2024)."},{"key":"3239_CR22","doi-asserted-by":"crossref","unstructured":"Hsu, Chung-Chian I-Z, Wu, Shih-Mao L. Decoding AI Complexity: SHAP Textual Explanations via LLM for Improved Model Transparency. 2024 International Conference on Consumer Electronics-Taiwan (ICCE-Taiwan). IEEE, 2024.","DOI":"10.1109\/ICCE-Taiwan62264.2024.10674465"},{"key":"3239_CR23","first-page":"24824","volume":"35","author":"J Wei","year":"2022","unstructured":"Wei J, et al. Chain-of-thought prompting elicits reasoning in large Language models. Adv Neural Inf Process Syst. 2022;35:24824\u201337.","journal-title":"Adv Neural Inf Process Syst"},{"issue":"1","key":"3239_CR24","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1038\/s41746-023-00837-4","volume":"6","author":"N Bienefeld","year":"2023","unstructured":"Bienefeld N, et al. Solving the explainable AI conundrum by bridging clinicians\u2019 needs and developers\u2019 goals. NPJ Digit Med. 2023;6(1):94.","journal-title":"NPJ Digit Med"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-025-03239-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-025-03239-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-025-03239-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T15:36:51Z","timestamp":1764171411000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-025-03239-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,26]]},"references-count":24,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["3239"],"URL":"https:\/\/doi.org\/10.1186\/s12911-025-03239-6","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,26]]},"assertion":[{"value":"11 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The Institutional Review Board of the College of Medicine, The Catholic University of Korea, reviewed the study protocol and determined that it met the criteria for exemption from review. The study used the publicly available MIMIC-III database, which is accessible only to credentialed researchers who have completed human-subjects training and signed a data use agreement. All analyses complied with this agreement. For the LLM evaluation, 40 test cases were sampled, with small perturbations (\u2264\u20093% random noise on numeric values and removal of all identifying metadata) applied to simulate synthetic-like examples. No protected health information (PHI) was used as input to the language model. The study therefore adhered to all applicable regulations and ethical standards governing the use of sensitive clinical data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"430"}}