{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T16:30:52Z","timestamp":1787243452038,"version":"build-2736575974"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T00:00:00Z","timestamp":1779667200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"vor","delay-in-days":56,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Neurol"],"DOI":"10.1186\/s12883-026-05005-1","type":"journal-article","created":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T07:54:57Z","timestamp":1779695697000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evaluating the performance of ChatGPT in responding to myotonic dystrophy type 1 patient inquiries: a specialist physician-based study"],"prefix":"10.1186","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-1170-4110","authenticated-orcid":false,"given":"G\u00fcl\u015fah","family":"\u00c7elik","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6555-2111","authenticated-orcid":false,"given":"Hanife Hale","family":"Hekim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3064-2878","authenticated-orcid":false,"given":"Meral Bilgilisoy","family":"Filiz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8141-4525","authenticated-orcid":false,"given":"Naciye F\u00fcsun","family":"Toraman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,25]]},"reference":[{"key":"5005_CR1","doi-asserted-by":"publisher","first-page":"1187","DOI":"10.1007\/s00167-023-07355-6","volume":"31","author":"J Dahmen","year":"2023","unstructured":"Dahmen J, Kayaalp ME, Ollivier M, Pareek A, Hirschmann MT, Karlsson J, et al. Artificial intelligence bot ChatGPT in medical research: the potential game changer as a double-edged sword. Knee Surg Sports Traumatol Arthrosc. 2023;31:1187\u20139. https:\/\/doi.org\/10.1007\/s00167-023-07355-6.","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"5005_CR2","doi-asserted-by":"publisher","unstructured":"Zhou Z. Evaluation of ChatGPT\u2019s Capabilities in Medical Report Generation. Cureus. 2023. https:\/\/doi.org\/10.7759\/cureus.37589.","DOI":"10.7759\/cureus.37589"},{"key":"5005_CR3","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/s10916-023-01925-4","volume":"47","author":"M Cascella","year":"2023","unstructured":"Cascella M, Montomoli J, Bellini V, Bignami E. Evaluating the feasibility of ChatGPT in healthcare: an analysis of multiple clinical and research scenarios. J Med Syst. 2023;47:33. https:\/\/doi.org\/10.1007\/s10916-023-01925-4.","journal-title":"J Med Syst"},{"key":"5005_CR4","doi-asserted-by":"publisher","first-page":"100173","DOI":"10.1016\/j.teler.2024.100173","volume":"16","author":"WAP Supriyono","year":"2024","unstructured":"Supriyono WAP, Suyono, Kurniawan F. Advancements in natural language processing: Implications, challenges, and future directions. Telematics Inf Rep. 2024;16:100173. https:\/\/doi.org\/10.1016\/j.teler.2024.100173.","journal-title":"Telematics Inf Rep"},{"key":"5005_CR5","doi-asserted-by":"publisher","unstructured":"Mitchell M, Krakauer DC. The debate over understanding in AI\u2019s large language models. Proceedings of the National Academy of Sciences. 2023;120. https:\/\/doi.org\/10.1073\/pnas.2215907120.","DOI":"10.1073\/pnas.2215907120"},{"key":"5005_CR6","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1001\/jamainternmed.2023.1838","volume":"183","author":"JW Ayers","year":"2023","unstructured":"Ayers JW, Poliak A, Dredze M, Leas EC, Zhu Z, Kelley JB, et al. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med. 2023;183:589. https:\/\/doi.org\/10.1001\/jamainternmed.2023.1838.","journal-title":"JAMA Intern Med"},{"key":"5005_CR7","doi-asserted-by":"publisher","unstructured":"Ahmed SK, Hussein S, Aziz TA, Chakraborty S, Islam MR, Dhama K. The power of ChatGPT in revolutionizing rural healthcare delivery. Health Sci Rep. 2023;6. https:\/\/doi.org\/10.1002\/hsr2.1684.","DOI":"10.1002\/hsr2.1684"},{"key":"5005_CR8","doi-asserted-by":"publisher","unstructured":"Montazeri M, Galavi Z, Ahmadian L. What are the applications of ChatGPT in healthcare: gain or loss? Health Sci Rep. 2024;7. https:\/\/doi.org\/10.1002\/hsr2.1878.","DOI":"10.1002\/hsr2.1878"},{"key":"5005_CR9","doi-asserted-by":"publisher","first-page":"100905","DOI":"10.1016\/j.lanwpc.2023.100905","volume":"41","author":"X Wang","year":"2023","unstructured":"Wang X, Sanders HM, Liu Y, Seang K, Tran BX, Atanasov AG, et al. ChatGPT: promise and challenges for deployment in low- and middle-income countries. Lancet Reg Health West Pac. 2023;41:100905. https:\/\/doi.org\/10.1016\/j.lanwpc.2023.100905.","journal-title":"Lancet Reg Health West Pac"},{"key":"5005_CR10","doi-asserted-by":"publisher","first-page":"1246","DOI":"10.1016\/j.apmr.2007.10.049","volume":"89","author":"C Gagnon","year":"2008","unstructured":"Gagnon C, Mathieu J, Jean S, Laberge L, Perron M, Veillette S, et al. Predictors of disrupted social participation in myotonic dystrophy type 1. Arch Phys Med Rehabil. 2008;89:1246\u201355. https:\/\/doi.org\/10.1016\/j.apmr.2007.10.049.","journal-title":"Arch Phys Med Rehabil"},{"key":"5005_CR11","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1111\/ane.13086","volume":"139","author":"AKT Holm\u00f8y","year":"2019","unstructured":"Holm\u00f8y AKT, Johannessen CH, Hope S, van Walsem MR, Aanonsen NO, Hassel B. Uncovering health and social care needs among myotonic dystrophy patients. Acta Neurol Scand. 2019;139:526\u201332. https:\/\/doi.org\/10.1111\/ane.13086.","journal-title":"Acta Neurol Scand"},{"key":"5005_CR12","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1016\/j.ncl.2014.04.011","volume":"32","author":"CA Thornton","year":"2014","unstructured":"Thornton CA. Myotonic dystrophy. Neurol Clin. 2014;32:705\u201319. https:\/\/doi.org\/10.1016\/j.ncl.2014.04.011.","journal-title":"Neurol Clin"},{"key":"5005_CR13","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s10897-014-9752-1","volume":"24","author":"A\u00d8 Geirdal","year":"2015","unstructured":"Geirdal A\u00d8, Lund-Petersen I, Heiberg A. Understanding the experience of myotonic dystrophy. Mixed method study. J Genet Couns. 2015;24:169\u201378. https:\/\/doi.org\/10.1007\/s10897-014-9752-1.","journal-title":"J Genet Couns"},{"key":"5005_CR14","doi-asserted-by":"publisher","first-page":"847","DOI":"10.1016\/j.nmd.2010.08.006","volume":"20","author":"C Gagnon","year":"2010","unstructured":"Gagnon C, Chouinard MC, Laberge L, Veillette S, B\u00e9gin P, Breton R, et al. Health supervision and anticipatory guidance in adult myotonic dystrophy type 1. Neuromuscul Disord. 2010;20:847\u201351. https:\/\/doi.org\/10.1016\/j.nmd.2010.08.006.","journal-title":"Neuromuscul Disord"},{"key":"5005_CR15","doi-asserted-by":"publisher","unstructured":"Kondylakis H, Kazantzaki E, Koumakis L, Genitsaridi I, Marias K, Gorini A, et al. Development of interactive empowerment services in support of personalised medicine. Ecancermedicalscience. 2014;8. https:\/\/doi.org\/10.3332\/ecancer.2014.400.","DOI":"10.3332\/ecancer.2014.400"},{"key":"5005_CR16","doi-asserted-by":"publisher","unstructured":"Callus E, Bertoldo EG, Beretta M, Boveri S, Cardani R, Fossati B, et al. Neuropsychological and psychological functioning aspects in myotonic dystrophy type 1 patients in Italy. Front Neurol. 2018;9. https:\/\/doi.org\/10.3389\/fneur.2018.00751.","DOI":"10.3389\/fneur.2018.00751"},{"key":"5005_CR17","doi-asserted-by":"publisher","first-page":"499","DOI":"10.34172\/apb.2024.060","volume":"14","author":"R Gummadi","year":"2024","unstructured":"Gummadi R, Dasari N, Kumar DS, Pindiprolu SKSS. Evaluating the accuracy of large language model (ChatGPT) in providing information on metastatic breast cancer. Adv Pharm Bull. 2024;14:499\u2013503. https:\/\/doi.org\/10.34172\/apb.2024.060.","journal-title":"Adv Pharm Bull"},{"key":"5005_CR18","doi-asserted-by":"publisher","first-page":"7626","DOI":"10.1038\/s41598-024-58514-9","volume":"14","author":"L Zhenzhu","year":"2024","unstructured":"Zhenzhu L, Jingfeng Z, Wei Z, Jianjun Z, Yinshui X. GPT-agents based on medical guidelines can improve the responsiveness and explainability of outcomes for traumatic brain injury rehabilitation. Sci Rep. 2024;14:7626. https:\/\/doi.org\/10.1038\/s41598-024-58514-9.","journal-title":"Sci Rep"},{"key":"5005_CR19","doi-asserted-by":"publisher","unstructured":"Giray E, Illeez \u00d6G, Korkmaz MD, Capan N, Karadag Saygi E, Ayd\u0131n R. Assessing the accuracy and reproducibility of artificial intelligence-generated medical responses by ChatGPT on Scheuermann's kyphosis. Turk J Phys Med Rehabil. 2024;71(4):457\u201364. https:\/\/doi.org\/10.5606\/tftrd.2025.15876.","DOI":"10.5606\/tftrd.2025.15876"},{"key":"5005_CR20","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1016\/j.jseint.2025.01.008","volume":"9","author":"CK Johnson","year":"2025","unstructured":"Johnson CK, Mandalia K, Corban J, Beall KE, Shah SS. Adequacy of ChatGPT responses to frequently asked questions about shoulder arthroplasty: is it an appropriate adjunct for patient education? JSES Int. 2025;9:830\u20136. https:\/\/doi.org\/10.1016\/j.jseint.2025.01.008.","journal-title":"JSES Int"},{"key":"5005_CR21","doi-asserted-by":"publisher","first-page":"e70014","DOI":"10.2196\/70014","volume":"12","author":"L Wang","year":"2025","unstructured":"Wang L, Bhanushali T, Huang Z, Yang J, Badami S, Hightow-Weidman L. Evaluating generative AI in mental health: systematic review of capabilities and limitations. JMIR Ment Health. 2025;12:e70014\u201370014. https:\/\/doi.org\/10.2196\/70014.","journal-title":"JMIR Ment Health"},{"key":"5005_CR22","doi-asserted-by":"crossref","unstructured":"Kojima T, Gu SS, Reid M, Matsuo Y, Iwasawa Y. Large Language Models are Zero-Shot Reasoners. Advances in neural information processing systems. 2022;35:22199\u2013213.","DOI":"10.52202\/068431-1613"},{"key":"5005_CR23","doi-asserted-by":"publisher","first-page":"169","DOI":"10.52312\/jdrs.2023.1402","volume":"35","author":"D Yapar","year":"2024","unstructured":"Yapar D, Demir Avc\u0131 Y, Tokur Sonuvar E, Faruk E\u011ferci \u00d6, Yapar A. ChatGPT\u2019s potential to support home care for patients in the early period after orthopedic interventions and enhance public health. Jt Dis Relat Surg. 2024;35:169\u201376. https:\/\/doi.org\/10.52312\/jdrs.2023.1402.","journal-title":"Jt Dis Relat Surg"},{"key":"5005_CR24","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1038\/s41746-024-01258-7","volume":"7","author":"TYC Tam","year":"2024","unstructured":"Tam TYC, Sivarajkumar S, Kapoor S, Stolyar AV, Polanska K, McCarthy KR, et al. A framework for human evaluation of large language models in healthcare derived from literature review. NPJ Digit Med. 2024;7:258. https:\/\/doi.org\/10.1038\/s41746-024-01258-7.","journal-title":"NPJ Digit Med"},{"key":"5005_CR25","doi-asserted-by":"publisher","first-page":"222","DOI":"10.5152\/j.aott.2025.25279","volume":"59","author":"S Ya\u015f","year":"2025","unstructured":"Ya\u015f S, Yapar D, Yapar A, \u00d6zel T, Tokg\u00f6z MA, Baymurat AC, et al. Assessing the role of large language models in adolescent idiopathic scoliosis care: a comparison between ChatGPT and Google Gemini. Acta Orthop Traumatol Turc. 2025;59:222\u20139. https:\/\/doi.org\/10.5152\/j.aott.2025.25279.","journal-title":"Acta Orthop Traumatol Turc"},{"key":"5005_CR26","doi-asserted-by":"publisher","first-page":"18","DOI":"10.3390\/encyclopedia5010018","volume":"5","author":"M Koo","year":"2025","unstructured":"Koo M, Yang S-W, Likert-Type Scale. Encyclopedia. 2025;5:18. https:\/\/doi.org\/10.3390\/encyclopedia5010018.","journal-title":"Encyclopedia"},{"key":"5005_CR27","first-page":"10","volume":"7","author":"BMLJA Moskal","year":"2019","unstructured":"Moskal BMLJA. Scoring rubric development: validity and reliability. Practical assessment. Res evaluation. 2019;7:10.","journal-title":"Res evaluation"},{"key":"5005_CR28","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1002\/jhm.898","volume":"6","author":"RR Khanna","year":"2011","unstructured":"Khanna RR, Karliner LS, Eck M, Vittinghoff E, Koenig CJ, Fang MC. Performance of an online translation tool when applied to patient educational material. J Hosp Med. 2011;6:519\u201325. https:\/\/doi.org\/10.1002\/jhm.898.","journal-title":"J Hosp Med"},{"key":"5005_CR29","doi-asserted-by":"publisher","first-page":"e13","DOI":"10.2196\/diabetes.7446","volume":"2","author":"X Chen","year":"2017","unstructured":"Chen X, Acosta S, Barry AE. Machine or human? Evaluating the quality of a language translation mobile app for diabetes education material. JMIR Diabetes. 2017;2:e13. https:\/\/doi.org\/10.2196\/diabetes.7446.","journal-title":"JMIR Diabetes"},{"key":"5005_CR30","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1177\/0748175613513808","volume":"47","author":"C Ayre","year":"2014","unstructured":"Ayre C, Scally AJ. Critical values for lawshe\u2019s content validity ratio. Meas Evaluation Couns Dev. 2014;47:79\u201386. https:\/\/doi.org\/10.1177\/0748175613513808.","journal-title":"Meas Evaluation Couns Dev"},{"key":"5005_CR31","unstructured":"Yurdug\u00fcl H. \u00d6l\u00e7ek geli\u015ftirme \u00e7al\u0131\u015fmalar\u0131nda kapsam ge\u00e7erli\u011fi i\u00e7in kapsam ge\u00e7erlik indekslerinin kullan\u0131lmas\u0131. In: XIV Ulusal E\u011fitim Bilimleri Kongresi; 28\u201330 September 2005; Denizli, T\u00fcrkiye. Pamukkale \u00dcniversitesi E\u011fitim Fak\u00fcltesi; 2005. p. 771\u2013774."},{"key":"5005_CR32","doi-asserted-by":"publisher","first-page":"165","DOI":"10.15171\/jcs.2015.017","volume":"4","author":"V Zamanzadeh","year":"2015","unstructured":"Zamanzadeh V, Ghahramanian A, Rassouli M, Abbaszadeh A, Alavi-Majd H, Nikanfar A-R. Design and implementation content validity study: development of an instrument for measuring patient-centered communication. J Caring Sci. 2015;4:165\u201378. https:\/\/doi.org\/10.15171\/jcs.2015.017.","journal-title":"J Caring Sci"},{"key":"5005_CR33","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1002\/nur.20147","volume":"29","author":"DF Polit","year":"2006","unstructured":"Polit DF, Beck CT. The content validity index: Are you sure you know what\u2019s being reported? critique and recommendations. Res Nurs Health. 2006;29:489\u201397. https:\/\/doi.org\/10.1002\/nur.20147.","journal-title":"Res Nurs Health"},{"key":"5005_CR34","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1038\/s44172-024-00271-8","volume":"3","author":"S Wang","year":"2024","unstructured":"Wang S, Zhao Z, Ouyang X, Liu T, Wang Q, Shen D. Interactive computer-aided diagnosis on medical image using large language models. Commun Eng. 2024;3:133. https:\/\/doi.org\/10.1038\/s44172-024-00271-8.","journal-title":"Commun Eng"},{"key":"5005_CR35","doi-asserted-by":"publisher","first-page":"4374","DOI":"10.1007\/s00330-024-11339-6","volume":"35","author":"S Lee","year":"2025","unstructured":"Lee S, Youn J, Kim H, Kim M, Yoon SH. CXR-LLaVA: a multimodal large language model for interpreting chest X-ray images. Eur Radiol. 2025;35:4374\u201386. https:\/\/doi.org\/10.1007\/s00330-024-11339-6.","journal-title":"Eur Radiol"},{"key":"5005_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5468\/ogs.24231","volume":"68","author":"JY Han","year":"2025","unstructured":"Han JY. Usefulness and limitations of Chat GPT in getting information on teratogenic drugs exposed in pregnancy. Obstet Gynecol Sci. 2025;68:1\u20138. https:\/\/doi.org\/10.5468\/ogs.24231.","journal-title":"Obstet Gynecol Sci"},{"key":"5005_CR37","doi-asserted-by":"publisher","first-page":"1343","DOI":"10.1111\/1756-185X.14749","volume":"26","author":"C Uz","year":"2023","unstructured":"Uz C, Umay E. Dr ChatGPT: Is it a reliable and useful source for common rheumatic diseases? Int J Rheum Dis. 2023;26:1343\u20139. https:\/\/doi.org\/10.1111\/1756-185X.14749.","journal-title":"Int J Rheum Dis"},{"key":"5005_CR38","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.46736","author":"RE Cankurtaran","year":"2023","unstructured":"Cankurtaran RE, Polat YH, Aydemir NG, Umay E, Yurekli OT. Reliability and usefulness of ChatGPT for inflammatory bowel diseases: an analysis for patients and healthcare professionals. Cureus. 2023. https:\/\/doi.org\/10.7759\/cureus.46736.","journal-title":"Cureus"},{"key":"5005_CR39","doi-asserted-by":"publisher","unstructured":"Wang Y, Yang S, Zeng C, Xie Y, Shen Y, Li J, et al. Evaluating the performance of ChatGPT in patient consultation and image-based preliminary diagnosis in thyroid eye disease. Front Med (Lausanne). 2025;12. https:\/\/doi.org\/10.3389\/fmed.2025.1546706.","DOI":"10.3389\/fmed.2025.1546706"},{"key":"5005_CR40","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1177\/19322968231203987","volume":"19","author":"SA Meo","year":"2025","unstructured":"Meo SA, Al-Khlaiwi T, AbuKhalaf AA, Meo AS, Klonoff DC. The scientific knowledge of bard and ChatGPT in endocrinology, diabetes, and diabetes technology: multiple-choice questions examination-based performance. J Diabetes Sci Technol. 2025;19:705\u201310. https:\/\/doi.org\/10.1177\/19322968231203987.","journal-title":"J Diabetes Sci Technol"},{"key":"5005_CR41","doi-asserted-by":"publisher","first-page":"e00765","DOI":"10.14309\/ctg.0000000000000765","volume":"15","author":"A Toiv","year":"2024","unstructured":"Toiv A, Saleh Z, Ishak A, Alsheik E, Venkat D, Nandi N, et al. Digesting digital health: a study of appropriateness and readability of ChatGPT-generated gastroenterological information. Clin Transl Gastroenterol. 2024;15:e00765. https:\/\/doi.org\/10.14309\/ctg.0000000000000765.","journal-title":"Clin Transl Gastroenterol"},{"key":"5005_CR42","doi-asserted-by":"publisher","first-page":"e39250","DOI":"10.1097\/MD.0000000000039250","volume":"103","author":"A Fatima","year":"2024","unstructured":"Fatima A, Shafique MA, Alam K, Fadlalla Ahmed TK, Mustafa MS. ChatGPT in medicine: A cross-disciplinary systematic review of ChatGPT\u2019s (artificial intelligence) role in research, clinical practice, education, and patient interaction. Medicine. 2024;103:e39250. https:\/\/doi.org\/10.1097\/MD.0000000000039250.","journal-title":"Medicine"},{"key":"5005_CR43","doi-asserted-by":"publisher","unstructured":"Atik O\u015e, Related Surgery (JDRS). Writing for Joint Diseases and : There is something new and interesting in this article! Jt Dis Relat Surg. 2023;34:533\u2013533. https:\/\/doi.org\/10.52312\/jdrs.2023.57916.","DOI":"10.52312\/jdrs.2023.57916"},{"key":"5005_CR44","doi-asserted-by":"publisher","first-page":"887","DOI":"10.3390\/healthcare11060887","volume":"11","author":"M Sallam","year":"2023","unstructured":"Sallam M. ChatGPT utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns. Healthcare. 2023;11:887. https:\/\/doi.org\/10.3390\/healthcare11060887.","journal-title":"Healthcare"},{"key":"5005_CR45","doi-asserted-by":"publisher","first-page":"297","DOI":"10.4103\/indianjpsychiatry.indianjpsychiatry_112_23","volume":"65","author":"OP Singh","year":"2023","unstructured":"Singh OP. Artificial intelligence in the era of ChatGPT - Opportunities and challenges in mental health care. Indian J Psychiatry. 2023;65:297\u20138. https:\/\/doi.org\/10.4103\/indianjpsychiatry.indianjpsychiatry_112_23.","journal-title":"Indian J Psychiatry"},{"key":"5005_CR46","doi-asserted-by":"publisher","first-page":"1790","DOI":"10.1007\/s11695-023-06603-5","volume":"33","author":"JS Samaan","year":"2023","unstructured":"Samaan JS, Yeo YH, Rajeev N, Hawley L, Abel S, Ng WH, et al. Assessing the accuracy of responses by the language model ChatGPT to questions regarding bariatric surgery. Obes Surg. 2023;33:1790\u20136. https:\/\/doi.org\/10.1007\/s11695-023-06603-5.","journal-title":"Obes Surg"},{"key":"5005_CR47","doi-asserted-by":"publisher","first-page":"838","DOI":"10.1097\/RLU.0000000000004665","volume":"48","author":"P Sharma","year":"2023","unstructured":"Sharma P. Chatbots in medical research. Clin Nucl Med. 2023;48:838\u20139. https:\/\/doi.org\/10.1097\/RLU.0000000000004665.","journal-title":"Clin Nucl Med"}],"container-title":["BMC Neurology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12883-026-05005-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12883-026-05005-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12883-026-05005-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T17:02:39Z","timestamp":1784566959000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12883-026-05005-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,25]]},"references-count":47,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["5005"],"URL":"https:\/\/doi.org\/10.1186\/s12883-026-05005-1","relation":{},"ISSN":["1471-2377"],"issn-type":[{"value":"1471-2377","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,25]]},"assertion":[{"value":"10 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 May 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This study was approved by the University of Health Sciences Antalya Training and Research Hospital Clinical Research Ethics Committee (Approval Date: January 30, 2025; Approval Number: 2\/15). Informed consent was obtained from all participants included in the study. All procedures performed in studies involving human participants were conducted in accordance with the ethical standards of the institutional and\/or national research committee and with the 2013 Declaration of Helsinki and its later amendments or comparable ethical standards.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"471"}}