{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,13]],"date-time":"2026-11-13T00:13:02Z","timestamp":1794528782819,"version":"4.9.1"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T00:00:00Z","timestamp":1778889600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"vor","delay-in-days":55,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Recep Tayyip Erdo\u011fan University Development Foundation","award":["02026003011179"],"award-info":[{"award-number":["02026003011179"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Emerg Med"],"DOI":"10.1186\/s12873-026-01616-6","type":"journal-article","created":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T13:04:36Z","timestamp":1778936676000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Diagnostic accuracy of AI-assisted point-of-care ultrasound for abdominal free fluid detection in FAST trauma assessment: a systematic review and meta-analysis"],"prefix":"10.1186","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2363-1844","authenticated-orcid":false,"given":"Ali","family":"\u00c7elik","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4018-302X","authenticated-orcid":false,"given":"Ensar","family":"Topalo\u011flu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1957-7283","authenticated-orcid":false,"given":"M\u00fcmin Murat","family":"Yaz\u0131c\u0131","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,16]]},"reference":[{"key":"1616_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacr.2020.01.024","author":"JY Shyu","year":"2020","unstructured":"Shyu JY, Khurana B, Soto JA, Biffl WL, Camacho MA, Diercks DB, et al. ACR Appropriateness Criteria\u00ae Major Blunt Trauma. J Am Coll Radiol. 2020. https:\/\/doi.org\/10.1016\/j.jacr.2020.01.024. 17.","journal-title":"J Am Coll Radiol"},{"key":"1616_CR2","doi-asserted-by":"publisher","unstructured":"Natarajan B, Gupta PK, Cemaj S, Sorensen M, Hatzoudis GI, Forse RA. FAST scan: is it worth doing in hemodynamically stable blunt trauma patients? Surgery. 2010;148. https:\/\/doi.org\/10.1016\/j.surg.2010.07.032.","DOI":"10.1016\/j.surg.2010.07.032"},{"key":"1616_CR3","doi-asserted-by":"publisher","unstructured":"The AIUM practice parameter for the performance of the extended. Focused assessment with sonography for trauma (EFAST). J Ultrasound Med. 2023;42. https:\/\/doi.org\/10.1002\/jum.16027.","DOI":"10.1002\/jum.16027"},{"key":"1616_CR4","doi-asserted-by":"publisher","unstructured":"Harel-Sterling M, Kwan C, Pirie J, Tessaro M, Cho DD, Coblentz A, et al. Competency standard derivation for point-of-care ultrasound image interpretation for emergency physicians. Ann Emerg Med. 2023;81. https:\/\/doi.org\/10.1016\/j.annemergmed.2022.11.002.","DOI":"10.1016\/j.annemergmed.2022.11.002"},{"key":"1616_CR5","doi-asserted-by":"publisher","unstructured":"Netherton S, Milenkovic V, Taylor M, Davis PJ. Diagnostic accuracy of eFAST in the trauma patient: A systematic review and meta-analysis. Can J Emerg Med. 2019;21. https:\/\/doi.org\/10.1017\/cem.2019.381.","DOI":"10.1017\/cem.2019.381"},{"key":"1616_CR6","doi-asserted-by":"publisher","unstructured":"Gamberini L, Scquizzato T, Tartaglione M, Chiarini V, Mazzoli CA, Allegri D, et al. Diagnostic accuracy for hemoperitoneum, influence on prehospital times and time-to-definitive treatment of prehospital FAST: a systematic review and individual participant data meta-analysis. Injury. 2023;54. https:\/\/doi.org\/10.1016\/j.injury.2023.03.024.","DOI":"10.1016\/j.injury.2023.03.024"},{"key":"1616_CR7","doi-asserted-by":"publisher","unstructured":"Stengel D, Leisterer J, Ferrada P, Ekkernkamp A, Mutze S, Hoenning A. Point-of-care ultrasonography for diagnosing thoracoabdominal injuries in patients with blunt trauma. Cochrane Database Syst Reviews. 2018;2018. https:\/\/doi.org\/10.1002\/14651858.CD012669.pub2.","DOI":"10.1002\/14651858.CD012669.pub2"},{"key":"1616_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajem.2017.11.019","author":"H Akoglu","year":"2018","unstructured":"Akoglu H, Celik OF, Celik A, Ergelen R, Onur O, Denizbasi A. Diagnostic accuracy of the Extended Focused Abdominal Sonography for Trauma (E-FAST) performed by emergency physicians compared to CT. Am J Emerg Med. 2018. https:\/\/doi.org\/10.1016\/j.ajem.2017.11.019.","journal-title":"Am J Emerg Med"},{"key":"1616_CR9","doi-asserted-by":"publisher","unstructured":"Buyurgan \u00c7S, Yarkac A, Bozkurt S, K\u00f6se A, Akverdi Akar G, Mete R, et al. Diagnostic accuracy of E-FAST examination performed by newly trained emergency physicians and its impact on clinical outcomes. BMC Emerg Med. 2025;25. https:\/\/doi.org\/10.1186\/s12873-025-01386-7.","DOI":"10.1186\/s12873-025-01386-7"},{"key":"1616_CR10","doi-asserted-by":"publisher","unstructured":"Lin K, Te, Lin ZY, Huang CC, Yu SY, Huang JL, Lin JH, et al. Prehospital ultrasound scanning for abdominal free fluid detection in trauma patients: a systematic review and meta-analysis. BMC Emerg Med. 2024;24. https:\/\/doi.org\/10.1186\/s12873-023-00919-2.","DOI":"10.1186\/s12873-023-00919-2"},{"key":"1616_CR11","doi-asserted-by":"publisher","unstructured":"Nasr Isfahani M, Nasri Nasrabadi E, Rabiei Z, Fatemi NAS, Heydari F. Enhancing clinical risk assessment in pediatric blunt abdominal trauma: a novel scoring system using ultrasound and laboratory data. BMC Emerg Med. 2025;25. https:\/\/doi.org\/10.1186\/s12873-025-01196-x.","DOI":"10.1186\/s12873-025-01196-x"},{"key":"1616_CR12","doi-asserted-by":"publisher","unstructured":"Hellenthal KEM, Porschen C, Wnent J, Lange M. Evolving role of point-of-care ultrasound in prehospital emergency care: a narrative review. Scand J Trauma Resusc Emerg Med. 2025;33. https:\/\/doi.org\/10.1186\/s13049-025-01443-x.","DOI":"10.1186\/s13049-025-01443-x"},{"key":"1616_CR13","doi-asserted-by":"publisher","unstructured":"Kim DJ, Burton JE, Hammad A, Sabhaney V, Freder J, Bone JN, et al. Test characteristics of ultrasound for the diagnosis of peritonsillar abscess: a systematic review and meta-analysis. Acad Emerg Med. 2023;30. https:\/\/doi.org\/10.1111\/acem.14660.","DOI":"10.1111\/acem.14660"},{"key":"1616_CR14","doi-asserted-by":"publisher","unstructured":"\u00c7elik A, Topalo\u011flu E, Yaz\u0131c\u0131 MM. Diagnostic accuracy of point-of-care ultrasound for diverticulitis: a systematic review and meta-analysis. BMC Emerg Med. 2026;26. https:\/\/doi.org\/10.1186\/s12873-025-01431-5.","DOI":"10.1186\/s12873-025-01431-5"},{"key":"1616_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/s11739-025-04255-0","author":"A \u00c7elik","year":"2026","unstructured":"\u00c7elik A, Hamdio\u011flu E. Test characteristics of emergency physician-performed point-of-care ultrasound for the diagnosis of intrauterine pregnancy: a systematic review and meta-analysis. Intern Emerg Med. 2026. https:\/\/doi.org\/10.1007\/s11739-025-04255-0.","journal-title":"Intern Emerg Med"},{"key":"1616_CR16","doi-asserted-by":"publisher","DOI":"10.1097\/TA.0000000000004021","author":"BE Levy","year":"2023","unstructured":"Levy BE, Castle JT, Virodov A, Wilt WS, Bumgardner C, Brim T, et al. Artificial intelligence evaluation of focused assessment with sonography in trauma. J Trauma Acute Care Surg. 2023. https:\/\/doi.org\/10.1097\/TA.0000000000004021.","journal-title":"J Trauma Acute Care Surg"},{"key":"1616_CR17","doi-asserted-by":"publisher","unstructured":"Aggarwal R, Sounderajah V, Martin G, Ting DSW, Karthikesalingam A, King D, et al. Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis. npj Digit Med. 2021;4. https:\/\/doi.org\/10.1038\/s41746-021-00438-z.","DOI":"10.1038\/s41746-021-00438-z"},{"key":"1616_CR18","doi-asserted-by":"publisher","unstructured":"Leo MM, Potter IY, Zahiri M, Vaziri A, Jung CF, Feldman JA. Using deep learning to detect the presence and location of hemoperitoneum on the focused assessment with sonography in trauma (FAST) examination in adults. J Digit Imaging. 2023;36. https:\/\/doi.org\/10.1007\/s10278-023-00845-6.","DOI":"10.1007\/s10278-023-00845-6"},{"key":"1616_CR19","doi-asserted-by":"publisher","unstructured":"Sjogren AR, Leo MM, Feldman J, Gwin JT. Image segmentation and machine learning for detection of abdominal free fluid in focused assessment with sonography for trauma examinations: a pilot study. J Ultrasound Med. 2016;35. https:\/\/doi.org\/10.7863\/ultra.15.11017.","DOI":"10.7863\/ultra.15.11017"},{"key":"1616_CR20","doi-asserted-by":"publisher","unstructured":"Chiu IM, Lin CHR, Yau FFF, Cheng FJ, Pan HY, Lin XH, et al. Use of a deep-learning algorithm to guide novices in performing focused assessment with sonography in trauma. JAMA Netw Open. 2023;6. https:\/\/doi.org\/10.1001\/jamanetworkopen.2023.5102.","DOI":"10.1001\/jamanetworkopen.2023.5102"},{"key":"1616_CR21","doi-asserted-by":"publisher","unstructured":"\u00c7elik A, Yazici MM. The advancement of artificial intelligence in point-of-care ultrasound (POCUS): a bibliometric analysis. Sonography. 2026;13. https:\/\/doi.org\/10.1002\/sono.70023.","DOI":"10.1002\/sono.70023"},{"key":"1616_CR22","doi-asserted-by":"publisher","unstructured":"Salameh JP, Bossuyt PM, McGrath TA, Thombs BD, Hyde CJ, MacAskill P, et al. Preferred reporting items for systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA): explanation, elaboration, and checklist. BMJ. 2020;370. https:\/\/doi.org\/10.1136\/bmj.m2632.","DOI":"10.1136\/bmj.m2632"},{"key":"1616_CR23","doi-asserted-by":"publisher","unstructured":"Sounderajah V, Ashrafian H, Rose S, Shah NH, Ghassemi M, Golub R, et al. A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI. Nat Med. 2021;27. https:\/\/doi.org\/10.1038\/s41591-021-01517-0.","DOI":"10.1038\/s41591-021-01517-0"},{"key":"1616_CR24","doi-asserted-by":"publisher","unstructured":"Frank RA, Salameh JP, Islam N, Yang B, Murad MH, Mustafa R, et al. How to critically appraise and interpret systematic reviews and meta-analyses of diagnostic accuracy: a user guide. Radiology. 2023;307. https:\/\/doi.org\/10.1148\/RADIOL.221437.","DOI":"10.1148\/RADIOL.221437"},{"key":"1616_CR25","doi-asserted-by":"publisher","unstructured":"Zhou Y, Dendukuri N. Statistics for quantifying heterogeneity in univariate and bivariate meta-analyses of binary data: The case of meta-analyses of diagnostic accuracy. Stat Med. 2014;33. https:\/\/doi.org\/10.1002\/sim.6115.","DOI":"10.1002\/sim.6115"},{"key":"1616_CR26","doi-asserted-by":"publisher","unstructured":"Lin Z, Li Z, Cao P, Lin Y, Liang F, He J, et al. Deep learning for emergency ascites diagnosis using ultrasonography images. J Appl Clin Med Phys. 2022;23. https:\/\/doi.org\/10.1002\/acm2.13695.","DOI":"10.1002\/acm2.13695"},{"key":"1616_CR27","doi-asserted-by":"publisher","unstructured":"Cheng CY, Chiu IM, Hsu MY, Pan HY, Tsai CM, Lin CHR. Deep learning assisted detection of abdominal free fluid in morison\u2019s pouch during focused assessment with sonography in trauma. Front Med (Lausanne). 2021;8. https:\/\/doi.org\/10.3389\/fmed.2021.707437.","DOI":"10.3389\/fmed.2021.707437"},{"key":"1616_CR28","doi-asserted-by":"publisher","unstructured":"Jeong D, Jeong W, Lee JH, Park SY. Use of automated machine learning for classifying hemoperitoneum on ultrasonographic images of morrison\u2019s pouch: a multicenter retrospective study. J Clin Med. 2023;12. https:\/\/doi.org\/10.3390\/jcm12124043.","DOI":"10.3390\/jcm12124043"},{"key":"1616_CR29","doi-asserted-by":"publisher","unstructured":"Y\u0131ld\u0131z Potter \u0130, Leo MM, Vaziri A, Feldman JA. Automated detection and localization of pericardial effusion from point-of-care cardiac ultrasound examination. Med Biol Eng Comput. 2023;61. https:\/\/doi.org\/10.1007\/s11517-023-02855-6.","DOI":"10.1007\/s11517-023-02855-6"},{"key":"1616_CR30","doi-asserted-by":"publisher","unstructured":"Yaz\u0131c\u0131 MM, Yava\u015fi \u00d6, \u00c7elik A, Altunta\u015f G, Altunta\u015f M, Bilir \u00d6, et al. The role of repeated extended FAST in patients with stable blunt thoracoabdominal trauma. Ulusal Travma ve Acil Cerrahi Dergisi. 2023;29. https:\/\/doi.org\/10.14744\/tjtes.2022.93529.","DOI":"10.14744\/tjtes.2022.93529"},{"key":"1616_CR31","doi-asserted-by":"publisher","DOI":"10.1002\/jcu.23846","author":"MM Yazici","year":"2024","unstructured":"Yazici MM, Yava\u015fi \u00d6. The development of point-of-care ultrasound (POCUS): Worldwide contributions and publication trends. J Clin Ultrasound. 2024. https:\/\/doi.org\/10.1002\/jcu.23846.","journal-title":"J Clin Ultrasound"},{"key":"1616_CR32","doi-asserted-by":"publisher","unstructured":"Hermann M, Hafner C, Scharner V, Hribersek M, Maleczek M, Schmid A, et al. Remote real-time supervision of prehospital point-of-care ultrasound: a feasibility study. Scand J Trauma Resusc Emerg Med. 2022;30. https:\/\/doi.org\/10.1186\/s13049-021-00985-0.","DOI":"10.1186\/s13049-021-00985-0"}],"container-title":["BMC Emergency Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12873-026-01616-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12873-026-01616-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12873-026-01616-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T23:38:26Z","timestamp":1783640306000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12873-026-01616-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,16]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1616"],"URL":"https:\/\/doi.org\/10.1186\/s12873-026-01616-6","relation":{},"ISSN":["1471-227X"],"issn-type":[{"value":"1471-227X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,16]]},"assertion":[{"value":"2 March 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 May 2026","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 and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"An abstract of this study was accepted for presentation at The Ultrasound Event | 2026 AIUM Annual Convention, Philadelphia, Pennsylvania, USA, May 27\u201330, 2026.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Previous presentation"}},{"value":"The principles outlined in the Declaration of Helsinki were followed.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human rights"}},{"value":"We formally registered the protocol in the PROSPERO database, ID: CRD420250615096, (Clinical trial number: not applicable).","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Registration"}},{"value":"During the preparation of this work, the authors used ChatGPT as a tool to refine the language, focusing on correcting typographical and grammatical errors. All edits and revisions were carefully reviewed and finalized by the authors, who take full responsibility for the content and accuracy of this publication.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Generative AI and AI-assisted technologies in the writing process"}},{"value":"The authors declare no competing interests.","order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"191"}}