{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T08:37:26Z","timestamp":1792744646960,"version":"4.5.0"},"reference-count":32,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","ejog.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["European Journal of Obstetrics & Gynecology and Reproductive Biology"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.ejogrb.2026.115495","type":"journal-article","created":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T23:57:23Z","timestamp":1792022243000},"page":"115495","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Impact of artificial intelligence in embryo selection to improve pregnancy rates per transfer in IVF cycles: a systematic review and meta-analysis"],"prefix":"10.1016","volume":"327","author":[{"given":"Samer","family":"Yaghi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francisco Fabregues","family":"Gasol","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan Jos\u00e9","family":"Espin\u00f3s","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miguel Angel","family":"Checa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alaa","family":"Owais","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed","family":"Fares","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paula Fabra","family":"Roca","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ejogrb.2026.115495_b0005","doi-asserted-by":"crossref","unstructured":"Alpha Scientists in Reproductive Medicine and ESHRE Special Interest Group of Embryology. The Istanbul consensus workshop on embryo assessment: proceedings of an expert meeting. Hum Reprod. 2011;26(6):1270\u20131283.","DOI":"10.1093\/humrep\/der037"},{"issue":"5","key":"10.1016\/j.ejogrb.2026.115495_b0010","first-page":"515","article-title":"Clinical relevance of assessments of embryo quality","volume":"31","author":"Racowsky","year":"2015","journal-title":"Reprod Biomed"},{"key":"10.1016\/j.ejogrb.2026.115495_b0015","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1038\/s41746-019-0096-y","article-title":"Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization","volume":"2","author":"Khosravi","year":"2019","journal-title":"npj Digit Med"},{"key":"10.1016\/j.ejogrb.2026.115495_b0020","article-title":"Application of convolutional neural networks in predicting embryo viability","volume":"135","author":"Yang","year":"2021","journal-title":"Comput Biol Med"},{"issue":"4","key":"10.1016\/j.ejogrb.2026.115495_b0025","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1093\/humrep\/deaa013","article-title":"Development of an artificial intelligence-based assessment model for embryo viability using static images captured by optical light microscopy during IVF","volume":"35","author":"VerMilyea","year":"2020","journal-title":"Hum Reprod"},{"issue":"3","key":"10.1016\/j.ejogrb.2026.115495_b0030","first-page":"330","article-title":"Development of an artificial intelligence-based assessment model for embryo viability","volume":"40","author":"VerMilyea","year":"2020","journal-title":"Reprod Biomed"},{"key":"10.1016\/j.ejogrb.2026.115495_b0035","article-title":"Performance of a deep learning neural network in selection of blastocysts for implantation","volume":"28","author":"Bormann","year":"2020","journal-title":"eClinicalMedicine"},{"issue":"9","key":"10.1016\/j.ejogrb.2026.115495_b0040","first-page":"1714","article-title":"Annotation-free embryo scoring with artificial intelligence: a multicenter, retrospective, cohort study","volume":"100","author":"Krag","year":"2021","journal-title":"Acta Obstet Gynecol Scand"},{"key":"10.1016\/j.ejogrb.2026.115495_b0065","first-page":"134","article-title":"Artificial intelligence outperforms embryologists in predicting embryo implantation using time-lapse videos","volume":"7","author":"Borna","year":"2024","journal-title":"Front Artif Intell"},{"issue":"2","key":"10.1016\/j.ejogrb.2026.115495_b0155","first-page":"456","article-title":"Clinical validation of KIDScore D5 for embryo selection: a multicenter observational study","volume":"122","author":"Papamentzelopoulou","year":"2024","journal-title":"Fertil Steril"},{"key":"10.1016\/j.ejogrb.2026.115495_b0150","first-page":"1234","article-title":"Artificial intelligence for blastocyst evaluation in IVF: a multicenter randomized controlled trial","volume":"30","author":"Illingworth","year":"2024","journal-title":"Nat Med"},{"key":"10.1016\/j.ejogrb.2026.115495_b0060","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1186\/s12884-021-04373-5","article-title":"A novel deep learning model for predicting live birth outcomes from time-lapse embryo images","volume":"22","author":"Huang","year":"2022","journal-title":"BMC Pregnancy Childbirth"},{"issue":"5","key":"10.1016\/j.ejogrb.2026.115495_b0075","first-page":"1342","article-title":"Evaluation of a deep learning-based scoring system (iDAScore v2.0) for predicting clinical outcomes of single vitrified-warmed blastocyst transfer","volume":"116","author":"Ueno","year":"2021","journal-title":"Fertil Steril"},{"issue":"2","key":"10.1016\/j.ejogrb.2026.115495_b0120","first-page":"187","article-title":"Ethical, clinical, and psychosocial considerations in the application of AI in reproductive medicine","volume":"45","author":"Dimitriadis","year":"2022","journal-title":"Reprod Biomed"},{"issue":"5","key":"10.1016\/j.ejogrb.2026.115495_b0140","first-page":"1045","article-title":"Artificial intelligence in embryo selection: challenges and opportunities","volume":"120","author":"Jiang","year":"2023","journal-title":"Fertil Steril"},{"issue":"9","key":"10.1016\/j.ejogrb.2026.115495_b0145","first-page":"2137","article-title":"Artificial intelligence in assisted reproduction: a review of current applications and future perspectives","volume":"10","author":"Sfakianoudis","year":"2022","journal-title":"Biomedicines"},{"issue":"5","key":"10.1016\/j.ejogrb.2026.115495_b0055","first-page":"1213","article-title":"Combining genetic screening and artificial intelligence for improved embryo selection","volume":"116","author":"Capalbo","year":"2021","journal-title":"Fertil Steril"},{"issue":"6","key":"10.1016\/j.ejogrb.2026.115495_b0080","first-page":"1027","article-title":"Predictive power of a deep learning model for embryo implantation: multicountry validation of iDAScore","volume":"43","author":"Lassen","year":"2021","journal-title":"Reprod Biomed"},{"key":"10.1016\/j.ejogrb.2026.115495_b0085","article-title":"The PRISMA 2020 statement: an updated guideline for reporting systematic reviews","volume":"372","author":"Page","year":"2021","journal-title":"BMJ"},{"issue":"1","key":"10.1016\/j.ejogrb.2026.115495_b0095","first-page":"59","article-title":"Clinical application of artificial intelligence in embryo selection: a systematic review","volume":"44","author":"Blank","year":"2022","journal-title":"Reprod Biomed"},{"key":"10.1016\/j.ejogrb.2026.115495_b0100","article-title":"Artificial intelligence in reproductive medicine: new era of individualized embryo selection","volume":"12","author":"Wang","year":"2021","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"1","key":"10.1016\/j.ejogrb.2026.115495_b0160","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1186\/s13643-016-0384-4","article-title":"Rayyan\u2014a web and mobile app for systematic reviews","volume":"5","author":"Ouzzani","year":"2016","journal-title":"Syst Rev"},{"key":"10.1016\/j.ejogrb.2026.115495_b0050","unstructured":"Higgins JPT, Thomas J, Chandler J, et al., editors. Cochrane Handbook for Systematic Reviews of Interventions Version 6.2 [updated February 2021]. Cochrane; 2021. Available from."},{"key":"10.1016\/j.ejogrb.2026.115495_b0090","article-title":"RoB 2: a revised tool for assessing risk of bias in randomized trials","volume":"366","author":"Sterne","year":"2019","journal-title":"BMJ"},{"key":"10.1016\/j.ejogrb.2026.115495_b0045","article-title":"The Newcastle\u2013Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses","author":"Wells","year":"2013","journal-title":"Ottawa Hospital Research Institute"},{"issue":"1","key":"10.1016\/j.ejogrb.2026.115495_b0105","first-page":"1","article-title":"Use of artificial intelligence in assisted reproductive technology: the future is now","volume":"14","author":"Nagori","year":"2021","journal-title":"J Hum Reprod Sci"},{"issue":"7304","key":"10.1016\/j.ejogrb.2026.115495_b0115","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1136\/bmj.323.7304.101","article-title":"Systematic reviews in health care: investigating publication bias","volume":"323","author":"Sterne","year":"2001","journal-title":"BMJ"},{"key":"10.1016\/j.ejogrb.2026.115495_b0070","first-page":"10234","article-title":"An artificial intelligence model trained on 181,428 embryos to predict implantation from time-lapse videos","volume":"13","author":"Lassen","year":"2023","journal-title":"Sci Rep"},{"issue":"7","key":"10.1016\/j.ejogrb.2026.115495_b0125","doi-asserted-by":"crossref","first-page":"1768","DOI":"10.1093\/humrep\/der106","article-title":"Association between the number of eggs and live birth in IVF treatment: analysis of 400,135 treatment cycles","volume":"26","author":"Sunkara","year":"2011","journal-title":"Hum Reprod"},{"issue":"1","key":"10.1016\/j.ejogrb.2026.115495_b0130","first-page":"12","article-title":"Impact of maternal age on oocyte and embryo competence","volume":"36","author":"Cimadomo","year":"2018","journal-title":"Reprod Biomed Online"},{"issue":"3","key":"10.1016\/j.ejogrb.2026.115495_b0135","first-page":"e59","article-title":"Reproductive outcomes in women using donor vs autologous oocytes: a systematic review and meta-analysis","volume":"116","author":"Esteves","year":"2021","journal-title":"Fertil Steril"},{"issue":"1","key":"10.1016\/j.ejogrb.2026.115495_b0110","first-page":"1","article-title":"ART: where have we come from and where are we going?","volume":"28","author":"Huyghe","year":"2022","journal-title":"Hum Reprod Update"}],"container-title":["European Journal of Obstetrics & Gynecology and Reproductive Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0301211526005634?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0301211526005634?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T07:39:12Z","timestamp":1792741152000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0301211526005634"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":32,"alternative-id":["S0301211526005634"],"URL":"https:\/\/doi.org\/10.1016\/j.ejogrb.2026.115495","relation":{},"ISSN":["0301-2115"],"issn-type":[{"value":"0301-2115","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Impact of artificial intelligence in embryo selection to improve pregnancy rates per transfer in IVF cycles: a systematic review and meta-analysis","name":"articletitle","label":"Article Title"},{"value":"European Journal of Obstetrics & Gynecology and Reproductive Biology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejogrb.2026.115495","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115495"}}