{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T08:12:59Z","timestamp":1774167179183,"version":"3.50.1"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"DOI":"10.1186\/s12911-025-03138-w","type":"journal-article","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T08:56:57Z","timestamp":1754557017000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A comparative study of screening performance between abstrackr and GPT models: Systematic review and contextual analysis"],"prefix":"10.1186","volume":"25","author":[{"given":"Sheyang","family":"Xu","sequence":"first","affiliation":[]},{"given":"Zhiheng","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Xingling","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Xiang-long","family":"Meng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,7]]},"reference":[{"key":"3138_CR1","doi-asserted-by":"crossref","unstructured":"Affengruber L, Van Der Maten MM, Spiero I, Nussbaumer-Streit B, Mahmi\u0107-Kaknjo M, Ellen ME, et al. An exploration of available methods and tools to improve the efficiency of systematic review production: a scoping review. BMC Med Res Methodol. 2024 Sep 18;24(1):210.","DOI":"10.1186\/s12874-024-02320-4"},{"key":"3138_CR2","doi-asserted-by":"crossref","unstructured":"Borah R, Brown AW, Capers PL, Kaiser KA. Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry. BMJ Open. 2017 Feb 27;7(2):e012545.","DOI":"10.1136\/bmjopen-2016-012545"},{"key":"3138_CR3","doi-asserted-by":"crossref","unstructured":"Cierco Jimenez R, Lee T, Rosillo N, Cordova R, Cree IA, Gonzalez A, et al. Machine learning computational tools to assist the performance of systematic reviews: a mapping review. BMC Med Res Methodol. 2022 Dec 16;22(1):322.","DOI":"10.1186\/s12874-022-01805-4"},{"key":"3138_CR4","doi-asserted-by":"crossref","unstructured":"Norman CR, Leeflang MMG, Porcher R, N\u00e9v\u00e9ol A. Measuring the impact of screening automation on meta-analyses of diagnostic test accuracy. Syst Rev. 2019 Oct 28;8(1):243.","DOI":"10.1186\/s13643-019-1162-x"},{"key":"3138_CR5","doi-asserted-by":"crossref","unstructured":"Issaiy M, Ghanaati H, Kolahi S, Shakiba M, Jalali AH, Zarei D, et al. Methodological insights into ChatGPT\u2019s screening performance in systematic reviews. BMC Med Res Methodol. 2024 Mar 27;24(1):78.","DOI":"10.1186\/s12874-024-02203-8"},{"key":"3138_CR6","doi-asserted-by":"crossref","unstructured":"Van Der Mierden S. Software tools for literature screening in systematic reviews in biomedical research. Altex. Internet]. 2019 [cited 2024 Oct 21]; Available from https:\/\/www.altex.org\/index.php\/altex\/article\/view\/1257.","DOI":"10.14573\/altex.1902131"},{"key":"3138_CR7","doi-asserted-by":"crossref","unstructured":"Masoumi S, Amirkhani H, Sadeghian N, Shahraz S. Natural language processing (NLP) to facilitate abstract review in medical research: the application of BioBERT to exploring the 20-year use of NLP in medical research. Syst Rev. 2024 Apr 15;13(1):107.","DOI":"10.1186\/s13643-024-02470-y"},{"key":"3138_CR8","doi-asserted-by":"publisher","unstructured":"Wallace BC, Small K, Brodley CE, Lau J, Trikalinos TA. Deploying an interactive machine learning system in an evidence-based practice center: abstrackr. In: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium [Internet]. Miami Florida USA: ACM; 2012 [2025 July 22]. p. 819\u201324. Available from https:\/\/doi.org\/10.1145\/2110363.2110464","DOI":"10.1145\/2110363.2110464"},{"key":"3138_CR9","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.jclinepi.2021.01.010","volume":"133","author":"X Qin","year":"2021","unstructured":"Qin X, Liu J, Wang Y, Liu Y, Deng K, Ma Y, et al. Natural language processing was effective in assisting rapid title and abstract screening when updating systematic reviews. J Clin Epidemiol. 2021 May;133:121\u201329.","journal-title":"J Clin Epidemiol"},{"key":"3138_CR10","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.jclinepi.2020.01.008","volume":"121","author":"J Clark","year":"2020","unstructured":"Clark J, Glasziou P, Del Mar C, Bannach-Brown A, Stehlik P, Scott AM. A full systematic review was completed in 2 weeks using automation tools: a case study. J Clin Epidemiol. 2020;121:81\u201390.","journal-title":"J Clin Epidemiol"},{"key":"3138_CR11","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.jclinepi.2018.12.001","volume":"108","author":"I Lerner","year":"2019","unstructured":"Lerner I, Cr\u00e9quit P, Ravaud P, Atal I. Automatic screening using word embeddings achieved high sensitivity and workload reduction for updating living network meta-analyses. J Clin Epidemiol. 2019;108:86\u201394.","journal-title":"J Clin Epidemiol"},{"key":"3138_CR12","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.jclinepi.2019.02.015","volume":"110","author":"R Bashir","year":"2019","unstructured":"Bashir R, Surian D, Dunn AG. The risk of conclusion change in systematic review updates can be estimated by learning from a database of published examples. J Clin Epidemiol. 2019;110:42\u201349.","journal-title":"J Clin Epidemiol"},{"key":"3138_CR13","doi-asserted-by":"crossref","unstructured":"Dennst\u00e4dt F, Zink J, Putora PM, Hastings J, Cihoric N. Title and abstract screening for literature reviews using large language models: an exploratory study in the biomedical domain. Syst Rev. 2024 Jun 15;13(1):158.","DOI":"10.1186\/s13643-024-02575-4"},{"issue":"1","key":"3138_CR14","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.artmed.2010.10.005","volume":"51","author":"O Frunza","year":"2011","unstructured":"Frunza O, Inkpen D, Matwin S, Klement W, O\u2019Blenis P. Exploiting the systematic review protocol for classification of medical abstracts. Artif Intell Med. 2011 Jan;51(1):17\u201325.","journal-title":"Artif Intell Med"},{"key":"3138_CR15","doi-asserted-by":"crossref","unstructured":"T\u00f3th B, Berek L, Gul\u00e1csi L, P\u00e9ntek M, Zrubka Z. Automation of systematic reviews of biomedical literature: a scoping review of studies indexed in PubMed. Syst Rev. 2024 Jul 8;13(1):174.","DOI":"10.1186\/s13643-024-02592-3"},{"issue":"7","key":"3138_CR16","doi-asserted-by":"publisher","first-page":"e072254","DOI":"10.1136\/bmjopen-2023-072254","volume":"13","author":"SHB Van Dijk","year":"2023","unstructured":"Van Dijk SHB, Brusse-Keizer MGJ, Bucs\u00e1n CC, Van Der Palen J, Doggen CJM, Lenferink A. Artificial intelligence in systematic reviews: promising when appropriately used. BMJ Open. 2023 Jul;13(7):e072254.","journal-title":"BMJ Open"},{"key":"3138_CR17","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.jclinepi.2022.05.017","volume":"149","author":"N Carey","year":"2022","unstructured":"Carey N, Harte M, Mc Cullagh L. A text-mining tool generated title-abstract screening workload savings: performance evaluation versus single-human screening. J Clin Epidemiol. 2022;149:53\u201359.","journal-title":"J Clin Epidemiol"},{"issue":"1","key":"3138_CR18","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1136\/injuryprev-2019-043247","volume":"26","author":"MJ Giummarra","year":"2020","unstructured":"Giummarra MJ, Lau G, Gabbe BJ. Evaluation of text mining to reduce screening workload for injury-focused systematic reviews. Inj Prev. 2020 Feb;26(1):55\u201360.","journal-title":"Inj Prev"},{"key":"3138_CR19","doi-asserted-by":"crossref","unstructured":"Rathbone J, Hoffmann T, Glasziou P. Faster title and abstract screening? Evaluating Abstrackr, a semi-automated online screening program for systematic reviewers. Syst Rev. 4:80. 2015 Jun 15.","DOI":"10.1186\/s13643-015-0067-6"},{"key":"3138_CR20","doi-asserted-by":"crossref","unstructured":"Gates A, Gates M, Sebastianski M, Guitard S, Elliott SA, Hartling L. The semi-automation of title and abstract screening: a retrospective exploration of ways to leverage Abstrackr\u2019s relevance predictions in systematic and rapid reviews. BMC Med Res Methodol. 2020 Jun 3;20(1):139.","DOI":"10.1186\/s12874-020-01031-w"},{"key":"3138_CR21","doi-asserted-by":"crossref","unstructured":"Gates A, Johnson C, Hartling L. Technology-assisted title and abstract screening for systematic reviews: a retrospective evaluation of the Abstrackr machine learning tool. Syst Rev. 2018 Mar 12;7(1):45.","DOI":"10.1186\/s13643-018-0707-8"},{"key":"3138_CR22","doi-asserted-by":"crossref","unstructured":"Dos Reis AHS, de Oliveira ALM, Fritsch C, Zouch J, Ferreira P, Polese JC. Usefulness of machine learning softwares to screen titles of systematic reviews: a methodological study. Syst Rev. 2023 Apr 15;12(1):68.","DOI":"10.1186\/s13643-023-02231-3"},{"issue":"1","key":"3138_CR23","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1186\/s13643-019-1222-2","volume":"8","author":"A Gates","year":"2019","unstructured":"Gates A, Guitard S, Pillay J, Elliott SA, Dyson MP, Newton AS, et al. Performance and usability of machine learning for screening in systematic reviews: a comparative evaluation of three tools. Syst Rev. 2019 Dec;8(1):278.","journal-title":"Syst Rev"},{"key":"3138_CR24","doi-asserted-by":"crossref","unstructured":"Chelli M, Descamps J, Lavou\u00e9 V, Trojani C, Azar M, Deckert M, et al. Hallucination rates and reference accuracy of chatgpt and bard for systematic reviews: comparative analysis, J Med Internet Res. 2024 May 22;26:e53164.","DOI":"10.2196\/53164"},{"key":"3138_CR25","doi-asserted-by":"crossref","unstructured":"Matsui K, Utsumi T, Aoki Y, Maruki T, Takeshima M, Takaesu Y. Human-comparable sensitivity of large language models in identifying eligible studies through title and abstract screening: 3-layer strategy using GPT-3.5 and GPT-4 for systematic reviews. J Med Internet Res. 2024 Aug 16;26:e52758..","DOI":"10.2196\/52758"},{"key":"3138_CR26","doi-asserted-by":"crossref","unstructured":"Li M, Sun J, Tan X. Evaluating the effectiveness of large language models in abstract screening: a comparative analysis. Syst Rev. 2024 Aug 21;13(1):219.","DOI":"10.1186\/s13643-024-02609-x"},{"key":"3138_CR27","doi-asserted-by":"crossref","unstructured":"Dai ZY, Wang FQ, Shen C, Ji YL, Li ZY, Wang Y, et al., Accuracy of large language models for literature screening in thoracic surgery: diagnostic study, J Med Internet Res, 2025 Mar 11;27:e67488.","DOI":"10.2196\/67488"},{"key":"3138_CR28","doi-asserted-by":"crossref","unstructured":"Chibwe K, Mantilla-Calderon D, Ling F. Evaluating GPT models for automated literature screening in wastewater-based epidemiology. ACS Environ Au. 2025 Jan 15;5(1):61\u201368.","DOI":"10.1021\/acsenvironau.4c00042"},{"issue":"2","key":"3138_CR29","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1002\/jrsm.1589","volume":"14","author":"MM Kebede","year":"2023","unstructured":"Kebede MM, Le Cornet C, Fortner RT. In-depth evaluation of machine learning methods for semi-automating article screening in a systematic review of mechanistic literature. Res Synth Methods. 2023 Mar;14(2):156\u201372.","journal-title":"Res Synth Methods"},{"issue":"1","key":"3138_CR30","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1186\/s13643-016-0384-4","volume":"5","author":"M Ouzzani","year":"2016","unstructured":"Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan\u2014a web and mobile app for systematic reviews. Syst Rev. 2016 Dec;5(1):210.","journal-title":"Syst Rev"},{"issue":"1","key":"3138_CR31","doi-asserted-by":"publisher","first-page":"e86277","DOI":"10.1371\/journal.pone.0086277","volume":"9","author":"T Bekhuis","year":"2014","unstructured":"Bekhuis T, Tseytlin E, Mitchell KJ, Demner-Fushman D.Feature engineering and a proposed decision-support system for systematic reviewers of medical evidence. PLoS One. 2014;9(1):e86277.","journal-title":"PLoS One"},{"key":"3138_CR32","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.jclinepi.2022.06.007","volume":"150","author":"GP Adam","year":"2022","unstructured":"Adam GP, Pappas D, Papageorgiou H, Evangelou E, Trikalinos TA. A novel tool that allows interactive screening of pubmed citations showed promise for the semi-automation of identification of biomedical literature. J Clin Epidemiol. 2022;150:63\u201371.","journal-title":"J Clin Epidemiol"},{"key":"3138_CR33","doi-asserted-by":"crossref","unstructured":"Bannach-Brown A, Przyby\u0142a P, Thomas J, Rice ASC, Ananiadou S, Liao J, et al. Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error. Syst Rev. 2019 Jan 15;8(1):23.","DOI":"10.1186\/s13643-019-0942-7"},{"key":"3138_CR34","doi-asserted-by":"publisher","first-page":"105531","DOI":"10.1016\/j.ijmedinf.2024.105531","volume":"189","author":"A Landschaft","year":"2024","unstructured":"Landschaft A, Antweiler D, Mackay S, Kugler S, R\u00fcping S, Wrobel S, et al. Implementation and evaluation of an additional GPT-4-based reviewer in PRISMA-based medical systematic literature reviews. Int J Med Inform. 2024 Sep;189:105531.","journal-title":"Int J Med Inform"},{"issue":"1","key":"3138_CR35","doi-asserted-by":"publisher","first-page":"e0227742","DOI":"10.1371\/journal.pone.0227742","volume":"15","author":"Z Wang","year":"2020","unstructured":"Wang Z, Nayfeh T, Tetzlaff J, O\u2019Blenis P, Murad MH. Error rates of human reviewers during abstract screening in systematic reviews. PLoS One. 2020;15(1):e0227742.","journal-title":"PLoS One"},{"key":"3138_CR36","doi-asserted-by":"crossref","unstructured":"Reichenpfader D, M\u00fcller H, Denecke K. Large language model-based information extraction from free-text radiology reports: a scoping review protocol. BMJ Open. 2023 Dec 9;13(12):e076865.","DOI":"10.1136\/bmjopen-2023-076865"},{"key":"3138_CR37","doi-asserted-by":"crossref","unstructured":"Brockmeier AJ, Ju M, Przyby\u0142a P, Ananiadou S. Improving reference prioritisation with PICO recognition. BMC Med Inform Decis Mak. 2019 Dec 5;19(1):256.","DOI":"10.1186\/s12911-019-0992-8"},{"key":"3138_CR38","doi-asserted-by":"crossref","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 (Baltimore). 2024 Aug 9;103(32):e39250.","DOI":"10.1097\/MD.0000000000039250"},{"issue":"3","key":"3138_CR39","doi-asserted-by":"publisher","first-page":"3713","DOI":"10.1007\/s11042-022-13428-4","volume":"82","author":"D Khurana","year":"2023","unstructured":"Khurana D, Koli A, Khatter K, Singh S. Natural language processing: state of the art, current trends and challenges. Multimed Tools Appl. 2023 Jan;82(3):3713\u201344.","journal-title":"Multimed Tools Appl"},{"key":"3138_CR40","doi-asserted-by":"crossref","unstructured":"Zimmerman J, Soler RE, Lavinder J, Murphy S, Atkins C, Hulbert L, et al. Iterative guided machine learning-assisted systematic literature reviews: a diabetes case study. Syst Rev. 2021 Apr 2;10(1):97.","DOI":"10.1186\/s13643-021-01640-6"},{"issue":"1","key":"3138_CR41","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1186\/s13643-021-01700-x","volume":"10","author":"B Pham","year":"2021","unstructured":"Pham B, Jovanovic J, Bagheri E, Antony J, Ashoor H, Nguyen TT, et al. Text mining to support abstract screening for knowledge syntheses: a semi-automated workflow. Syst Rev. 2021 Dec;10(1):156.","journal-title":"Syst Rev"},{"key":"3138_CR42","doi-asserted-by":"crossref","unstructured":"Dennstadt F, Zink J, Putora PM, et al. Syst Rev. 2024;13(1):158.","DOI":"10.1186\/s13643-024-02575-4"},{"key":"3138_CR43","doi-asserted-by":"crossref","unstructured":"Guo E, Gupta M, Deng J, Park YJ, Paget M, Naugler C. Automated Paper Screening for Clinical Reviews Using Large Language Models: data Analysis Study. J Med Internet Res. 2024 Jan 12;26:e48996.","DOI":"10.2196\/48996"},{"key":"3138_CR44","doi-asserted-by":"crossref","unstructured":"Wang L, Chen X, Deng X, et al. Npj Digit Med. 2024;7(1).","DOI":"10.1038\/s41746-024-01029-4"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-025-03138-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-025-03138-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-025-03138-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T15:01:15Z","timestamp":1757343675000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-025-03138-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"references-count":44,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["3138"],"URL":"https:\/\/doi.org\/10.1186\/s12911-025-03138-w","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]},"assertion":[{"value":"12 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 August 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":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"293"}}