{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T20:59:40Z","timestamp":1793307580794,"version":"4.5.0"},"reference-count":30,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Medical Informatics"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.ijmedinf.2026.106573","type":"journal-article","created":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T15:23:48Z","timestamp":1782401028000},"page":"106573","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":2,"special_numbering":"C","title":["Chain-of-verification prompting for NIH stroke scale extraction using small and frontier large language models"],"prefix":"10.1016","volume":"219","author":[{"given":"Jack","family":"Lott","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brett","family":"Stubbert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6321-0193","authenticated-orcid":false,"given":"David","family":"McShannon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"Bellissimo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3695-8108","authenticated-orcid":false,"given":"Dhruv","family":"Patel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1556-8343","authenticated-orcid":false,"given":"Nicholas","family":"Dietrich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ijmedinf.2026.106573_b0005","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.jphys.2013.12.012","article-title":"National institutes of health stroke scale (NIHSS)","volume":"60","author":"Kwah","year":"2014","journal-title":"J. Physiother."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0010","doi-asserted-by":"crossref","first-page":"864","DOI":"10.1161\/01.STR.20.7.864","article-title":"Measurements of acute cerebral infarction: a clinical examination scale","volume":"20","author":"Brott","year":"1989","journal-title":"Stroke"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0015","doi-asserted-by":"crossref","DOI":"10.1161\/JAHA.124.036386","article-title":"Automated extraction of stroke severity from unstructured electronic health records using natural language processing","author":"Fernandes","year":"2024","journal-title":"J. Am. Heart Assoc."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2023.102552","article-title":"Identifying stroke-related quantified evidence from electronic health records in real-world studies","volume":"140","author":"Yang","year":"2023","journal-title":"Artif. Intell. Med."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.jocn.2024.110847","article-title":"Large language models can effectively extract stroke and reperfusion audit data from medical free-text discharge summaries","volume":"129","author":"Goh","year":"2024","journal-title":"J. Clin. Neurosci."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0030","doi-asserted-by":"crossref","DOI":"10.1177\/08465371251323124","article-title":"Evaluating adherence to Canadian radiology guidelines for incidental hepatobiliary findings using RAG-enabled LLMs","author":"Dietrich","year":"2025","journal-title":"Can. Assoc. Radiol. J."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0035","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pdig.0001179","article-title":"Evaluating few-shot prompting for spectrogram-based lung sound classification using a multimodal language model","volume":"5","author":"Dietrich","year":"2026","journal-title":"PLOS Digital Health"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0040","doi-asserted-by":"crossref","DOI":"10.2214\/AJR.24.30928","article-title":"From bench to bedside with large language models: AJR expert panel narrative review","volume":"223","author":"Bhayana","year":"2024","journal-title":"Am. J. Roentgenol."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0045","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1038\/s41746-024-01157-x","article-title":"The ethics of ChatGPT in medicine and healthcare: a systematic review on Large Language Models (LLMs)","volume":"7","author":"Haltaufderheide","year":"2024","journal-title":"NPJ Digit Med"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0050","doi-asserted-by":"crossref","first-page":"189","DOI":"10.3390\/bdcc9070189","article-title":"State of the art and future directions of small language models: a systematic review","volume":"9","author":"Corradini","year":"2025","journal-title":"Big Data Cogn. Comput."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0055","doi-asserted-by":"crossref","DOI":"10.1093\/jamiaopen\/ooaf055","article-title":"Comparative analysis of large language models in clinical diagnosis: performance evaluation across common and complex medical cases","volume":"8","author":"Dinc","year":"2025","journal-title":"JAMIA Open"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0060","doi-asserted-by":"crossref","DOI":"10.2214\/AJR.25.32956","article-title":"Prompt engineering for large language models in interventional radiology","author":"Dietrich","year":"2025","journal-title":"Am. J. Roentgenol."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0065","doi-asserted-by":"crossref","DOI":"10.2214\/AJR.25.32956","article-title":"Advanced prompt engineering for large language models in interventional radiology: practical strategies and future perspectives","author":"Dietrich","year":"2025","journal-title":"Am. J. Roentgenol."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0070","doi-asserted-by":"crossref","unstructured":"Dhuliawala S, Komeili M, Xu J, Raileanu R, Li X, Celikyilmaz A, et al. Chain-of-verification reduces hallucination in large language models. ArXiv 2023.","DOI":"10.18653\/v1\/2024.findings-acl.212"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0075","series-title":"PhysioNet RRID:SCR_007345","article-title":"National institutes of health stroke scale (NIHSS) annotations for the MIMIC-III database (version 1.0.0)","author":"Wang","year":"2021"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0080","doi-asserted-by":"crossref","DOI":"10.1161\/01.CIR.101.23.e215","article-title":"PhysioBank, PhysioToolkit, and PhysioNet","volume":"101","author":"Goldberger","year":"2000","journal-title":"Circulation"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0085","series-title":"PhysioNet RRID:SCR_007345","article-title":"MIMIC-III clinical database (version 1.4)","author":"Johnson","year":"2016"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0090","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2025.38427","article-title":"Large language model assistant for emergency department discharge documentation","volume":"8","author":"Song","year":"2025","journal-title":"JAMA Netw. Open"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0095","doi-asserted-by":"crossref","first-page":"45239","DOI":"10.1038\/s41598-025-28767-z","article-title":"Human level information extraction from clinical reports with finetuned language models","volume":"15","author":"Liu","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0100","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1001\/archneur.1989.00520420080026","article-title":"Interrater reliability of the NIH stroke scale","volume":"46","author":"Goldstein","year":"1989","journal-title":"Arch. Neurol."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0105","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1159\/000016006","article-title":"Interrater reliability of the national institutes of health stroke scale: rating by neurologists and nurses in a community-based stroke incidence study","volume":"9","author":"Dewey","year":"1999","journal-title":"Cerebrovasc. Dis."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0110","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1038\/s41746-024-01233-2","article-title":"Privacy-preserving large language models for structured medical information retrieval","volume":"7","author":"Wiest","year":"2024","journal-title":"NPJ Digit. Med."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0115","doi-asserted-by":"crossref","first-page":"e428","DOI":"10.1016\/S2589-7500(24)00061-X","article-title":"Ethical and regulatory challenges of large language models in medicine","volume":"6","author":"Ong","year":"2024","journal-title":"Lancet Digit. Health"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0120","unstructured":"Schulhoff S, Ilie M, Balepur N, Kahadze K, Liu A, Si C, et al. The prompt report: A systematic survey of prompt engineering techniques 2024."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0125","doi-asserted-by":"crossref","first-page":"5101","DOI":"10.3390\/jcm13175101","article-title":"Large language model prompting techniques for advancement in clinical medicine","volume":"13","author":"Shah","year":"2024","journal-title":"J. Clin. Med."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0130","first-page":"1","article-title":"Retrieval-augmented generation: a practical guide for radiologists","author":"Dietrich","year":"2026","journal-title":"Roentgen. Ray Rev."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0135","doi-asserted-by":"crossref","first-page":"27446","DOI":"10.1038\/s41598-024-79110-x","article-title":"A fine-tuning enhanced RAG system with quantized influence measure as AI judge","volume":"14","author":"Rangan","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0140","series-title":"Proceedings of the 5th ACM International Conference on AI in Finance","first-page":"608","article-title":"Integrating knowledge graphs and vector retrieval augmented generation for efficient information extraction","author":"Sarmah","year":"2024"},{"key":"10.1016\/j.ijmedinf.2026.106573_b0145","doi-asserted-by":"crossref","DOI":"10.1093\/bjr\/tqaf173","article-title":"Agentic AI in radiology: emerging potential and unresolved challenges","author":"Dietrich","year":"2025","journal-title":"Br. J. Radiol."},{"key":"10.1016\/j.ijmedinf.2026.106573_b0150","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/S0140-6736(25)00202-8","article-title":"The rise of agentic AI teammates in medicine","volume":"405","author":"Zou","year":"2025","journal-title":"Lancet"}],"container-title":["International Journal of Medical Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386505626003138?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386505626003138?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T10:53:26Z","timestamp":1784112806000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1386505626003138"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":30,"alternative-id":["S1386505626003138"],"URL":"https:\/\/doi.org\/10.1016\/j.ijmedinf.2026.106573","relation":{},"ISSN":["1386-5056"],"issn-type":[{"value":"1386-5056","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Chain-of-verification prompting for NIH stroke scale extraction using small and frontier large language models","name":"articletitle","label":"Article Title"},{"value":"International Journal of Medical Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ijmedinf.2026.106573","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"106573"}}