{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T20:25:15Z","timestamp":1790367915782,"version":"4.1.0"},"reference-count":14,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,1,26]],"date-time":"2024-01-26T00:00:00Z","timestamp":1706227200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,1,26]],"date-time":"2024-01-26T00:00:00Z","timestamp":1706227200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Universit\u00e4tsmedizin Rostock"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Acta Neurochir"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Chat generative pre-trained transformer (GPT) is a novel large pre-trained natural language processing software that can enable scientific writing amongst a litany of other features. Given this, there is a growing interest in exploring the use of ChatGPT models as a modality to facilitate\/assist in the provision of clinical care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We investigated the time taken for the composition of neurosurgical discharge summaries and operative reports at a major University hospital. In so doing, we compared currently employed speech recognition software (i.e., SpeaKING) vs novel ChatGPT for three distinct neurosurgical diseases: chronic subdural hematoma, spinal decompression, and craniotomy. Furthermore, factual correctness was analyzed for the abovementioned diseases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The composition of neurosurgical discharge summaries and operative reports with the assistance of ChatGPT leads to a statistically significant time reduction across all three diseases\/report types:\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.001 for chronic subdural hematoma,\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.001 for decompression of spinal stenosis, and\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.001 for craniotomy and tumor resection. However, despite a high degree of factual correctness, the preparation of a surgical report for craniotomy proved to be significantly lower (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.002).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ChatGPT assisted in the writing of discharge summaries and operative reports as evidenced by an impressive reduction in time spent as compared to standard speech recognition software. While promising, the optimal use cases and ethics of AI-generated medical writing remain to be fully elucidated and must be further explored in future studies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00701-024-05908-3","type":"journal-article","created":{"date-parts":[[2024,1,26]],"date-time":"2024-01-26T02:02:07Z","timestamp":1706234527000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Leveraging artificial intelligence in neurosurgery\u2014unveiling ChatGPT for neurosurgical discharge summaries and operative reports"],"prefix":"10.1007","volume":"166","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5568-8429","authenticated-orcid":false,"given":"Daniel","family":"Dubinski","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sae-Yeon","family":"Won","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Svorad","family":"Trnovec","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bedjan","family":"Behmanesh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Baumgarten","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nazife","family":"Dinc","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juergen","family":"Konczalla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alvin","family":"Chan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua D.","family":"Bernstock","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas M.","family":"Freiman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florian","family":"Gessler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,1,26]]},"reference":[{"key":"5908_CR1","doi-asserted-by":"publisher","unstructured":"Baker A, Perov Y, Middleton K, Baxter J, Mullarkey D, Sangar D, Butt M, DoRosario A, Johri S (2020) A comparison of artificial intelligence and human doctors for the purpose of triage and diagnosis. Front Artif Intell. https:\/\/doi.org\/10.3389\/FRAI.2020.543405","DOI":"10.3389\/FRAI.2020.543405"},{"key":"5908_CR2","doi-asserted-by":"publisher","unstructured":"Bang Y, Cahyawijaya S, Lee N, et al (2023) A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity. AACL 2023, pp 45.\u00a0 \u00a0 https:\/\/doi.org\/10.48550\/arXiv.2302.04023","DOI":"10.48550\/arXiv.2302.04023"},{"key":"5908_CR3","unstructured":"ChatGPT banned in Italy over privacy concerns - BBC News. https:\/\/www.bbc.com\/news\/technology-65139406. Accessed 3 Apr 2023"},{"key":"5908_CR4","unstructured":"ChatGPT: how to use the AI chatbot taking over the world | Digital Trends. https:\/\/www.digitaltrends.com\/computing\/how-to-use-openai-chatgpt-text-generation-chatbot\/. Accessed 22 Jan 2023"},{"key":"5908_CR5","doi-asserted-by":"crossref","unstructured":"Gao CA, Howard FM, Markov NS, Dyer EC, Ramesh S, Luo Y, Pearson AT (2023) Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers.\u00a0NPJ Digit Med\u00a06(1):1\u20135","DOI":"10.1038\/s41746-023-00819-6"},{"key":"5908_CR6","doi-asserted-by":"publisher","unstructured":"Goldstein JA, Sastry G, Musser M, DiResta R, Gentzel M, Sedova K (2023) Generative language models and automated influence operations: emerging threats and potential mitigations, pp 82.\u00a0https:\/\/doi.org\/10.48550\/arXiv.2301.04246","DOI":"10.48550\/arXiv.2301.04246"},{"key":"5908_CR7","doi-asserted-by":"crossref","unstructured":"Juravle G, Boudouraki A, Terziyska M, Rezlescu C (2020) Trust in artificial intelligence for medical diagnoses. Prog Brain Res 253:263\u2013282","DOI":"10.1016\/bs.pbr.2020.06.006"},{"key":"5908_CR8","doi-asserted-by":"publisher","unstructured":"Korngiebel DM, Mooney SD (2021) Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery. NPJ Digit Med. https:\/\/doi.org\/10.1038\/S41746-021-00464-X","DOI":"10.1038\/S41746-021-00464-X"},{"key":"5908_CR9","doi-asserted-by":"crossref","unstructured":"Kung TH, Cheatham M, ChatGPT et al (2023) Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models.\u00a0PLOS Digit Heal 2(2):e0000198","DOI":"10.1371\/journal.pdig.0000198"},{"key":"5908_CR10","doi-asserted-by":"publisher","unstructured":"Ouyang L, Wu J, Jiang X, et al (2022) Training language models to follow instructions with human feedback. Adv Neural Inf Process Syst 35. https:\/\/doi.org\/10.48550\/arXiv.2203.02155","DOI":"10.48550\/arXiv.2203.02155"},{"issue":"3","key":"5908_CR11","doi-asserted-by":"publisher","first-page":"e107","DOI":"10.1016\/S2589-7500(23)00021-3","volume":"5","author":"SB Patel","year":"2023","unstructured":"Patel SB, Lam K (2023) ChatGPT: the future of discharge summaries? Lancet Digit Health 5(3):e107\u2013e108","journal-title":"Lancet Digit Health"},{"issue":"11","key":"5908_CR12","doi-asserted-by":"publisher","first-page":"753","DOI":"10.7326\/M16-0961","volume":"165","author":"C Sinsky","year":"2016","unstructured":"Sinsky C, Colligan L, Li L, Prgomet M, Reynolds S, Goeders L, Westbrook J, Tutty M, Blike G (2016) Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties. Ann Intern Med 165(11):753\u2013760","journal-title":"Ann Intern Med"},{"key":"5908_CR13","doi-asserted-by":"publisher","unstructured":"Stokel-Walker C (2022) AI bot ChatGPT writes smart essays - should professors worry? Nature. https:\/\/doi.org\/10.1038\/D41586-022-04397-7","DOI":"10.1038\/D41586-022-04397-7"},{"key":"5908_CR14","doi-asserted-by":"publisher","unstructured":"Zhang J, Wu J, Qiu Y, Song A, Li W, Li X, Liu Y (2023) Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: a review. Comput Biol Med. https:\/\/doi.org\/10.1016\/J.COMPBIOMED.2022.106517","DOI":"10.1016\/J.COMPBIOMED.2022.106517"}],"container-title":["Acta Neurochirurgica"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00701-024-05908-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00701-024-05908-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00701-024-05908-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T16:02:16Z","timestamp":1740153736000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00701-024-05908-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,26]]},"references-count":14,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["5908"],"URL":"https:\/\/doi.org\/10.1007\/s00701-024-05908-3","relation":{},"ISSN":["0942-0940"],"issn-type":[{"value":"0942-0940","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,26]]},"assertion":[{"value":"18 June 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 January 2024","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 authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"38"}}