{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T14:14:48Z","timestamp":1778854488781,"version":"3.51.4"},"reference-count":35,"publisher":"Elsevier BV","issue":"3","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T00:00:00Z","timestamp":1729209600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100016308","name":"Public Investment Bank France","doi-asserted-by":"publisher","award":["DOS0152872\/00"],"award-info":[{"award-number":["DOS0152872\/00"]}],"id":[{"id":"10.13039\/100016308","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","rbmojournal.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Reproductive BioMedicine Online"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.rbmo.2024.104493","type":"journal-article","created":{"date-parts":[[2024,10,19]],"date-time":"2024-10-19T22:13:26Z","timestamp":1729376006000},"page":"104493","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":2,"title":["Association between embryo development and early pregnancy loss revealed by artificial-intelligence-annotated kinetic events"],"prefix":"10.1016","volume":"51","author":[{"given":"Nina","family":"Gidel-Dissler","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thais","family":"Roque","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guillaume","family":"Canat","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benjamin","family":"Angelard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jessica","family":"Vandame","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandra","family":"Boussommier-Calleja","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.rbmo.2024.104493_bib0001","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1093\/humrep\/deu331","article-title":"The use of morphokinetics as a predictor of implantation: a multicentric study to define and validate an algorithm for embryo selection","volume":"30","author":"Basile","year":"2014","journal-title":"Hum. Reprod."},{"key":"10.1016\/j.rbmo.2024.104493_bib0002","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0262661","article-title":"Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences","volume":"17","author":"Berntsen","year":"2022","journal-title":"PLoS One"},{"key":"10.1016\/j.rbmo.2024.104493_bib0003","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1016\/j.rbmo.2013.02.006","article-title":"Modelling a risk classification of aneuploidy in human embryos using non-invasive morphokinetics","volume":"26","author":"Campbell","year":"2013","journal-title":"Reprod. Biomed. Online"},{"key":"10.1016\/j.rbmo.2024.104493_bib0004","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1007\/s10815-013-9992-2","article-title":"The use of morphokinetic parameters to select all embryos with full capacity to implant","volume":"30","author":"Chamayou","year":"2013","journal-title":"J. Assist. Reprod. Genet."},{"key":"10.1016\/j.rbmo.2024.104493_bib0005","doi-asserted-by":"crossref","unstructured":"Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., Bengio, Y., 2014. Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. arXiv [cs.CL]. https:\/\/doi.org\/10.48550\/arXiv.1406.1078","DOI":"10.3115\/v1\/D14-1179"},{"key":"10.1016\/j.rbmo.2024.104493_bib0006","doi-asserted-by":"crossref","first-page":"2650","DOI":"10.1093\/humrep\/deu278","article-title":"Proposed guidelines on the nomenclature and annotation of dynamic human embryo monitoring by a time-lapse user group","volume":"29","author":"Ciray","year":"2014","journal-title":"Hum. Reprod."},{"key":"10.1016\/j.rbmo.2024.104493_bib0007","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1016\/j.rbmo.2012.07.016","article-title":"Cleavage kinetics analysis of human embryos predicts development to blastocyst and implantation","volume":"25","author":"Dal Canto","year":"2012","journal-title":"Reprod. Biomed. Online"},{"issue":"Supplement 1","key":"10.1016\/j.rbmo.2024.104493_bib0008","article-title":"P-225 trustworthy AI algorithm for embryo ranking","volume":"38","author":"Deluga-Bia\u0142owarczuk","year":"2023","journal-title":"Hum. Reprod."},{"key":"10.1016\/j.rbmo.2024.104493_bib0009","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1186\/1477-7827-12-54","article-title":"Analysis of embryo morphokinetics, multinucleation and cleavage anomalies using continuous time-lapse monitoring in blastocyst transfer cycles","volume":"12","author":"Desai","year":"2014","journal-title":"Reprod. Biol. Endocrinol."},{"issue":"1","key":"10.1016\/j.rbmo.2024.104493_bib0035","article-title":"Artificial intelligence-powered assisted ranking of sibling embryos to increase first cycle pregnancy rate","volume":"49","author":"Dissler","year":"2024","journal-title":"RBMO"},{"key":"10.1016\/j.rbmo.2024.104493_bib0010","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1093\/humrep\/dead023","article-title":"A hybrid artificial intelligence model leverages multi-centric clinical data to improve fetal heart rate pregnancy prediction across time-lapse systems","volume":"38","author":"Duval","year":"2023","journal-title":"Hum. Reprod."},{"key":"10.1016\/j.rbmo.2024.104493_bib0011","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1016\/j.rbmo.2022.08.098","article-title":"Association between a deep learning-based scoring system with morphokinetics and morphological alterations in human embryos","volume":"45","author":"Ezoe","year":"2022","journal-title":"Reprod. Biomed. Online"},{"key":"10.1016\/j.rbmo.2024.104493_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.dib.2022.108258","article-title":"A time-lapse embryo dataset for morphokinetic parameter prediction","volume":"42","author":"Gomez","year":"2022","journal-title":"Data Brief"},{"key":"10.1016\/j.rbmo.2024.104493_bib0013","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.fertnstert.2011.11.042","article-title":"Selection of high-potential embryos by culture in poly(dimethylsiloxane) microwells and time-lapse imaging","volume":"97","author":"Hashimoto","year":"2012","journal-title":"Fertil. Steril."},{"key":"10.1016\/j.rbmo.2024.104493_bib0014","doi-asserted-by":"crossref","first-page":"90","DOI":"10.5653\/cerm.2017.44.2.90","article-title":"Evaluation of human embryo development in in vitro fertilization- and intracytoplasmic sperm injection-fertilized oocytes: A time-lapse study","volume":"44","author":"Kim","year":"2017","journal-title":"Clin. Exp. Reprod. Med."},{"key":"10.1016\/j.rbmo.2024.104493_bib0015","doi-asserted-by":"crossref","first-page":"2643","DOI":"10.1093\/humrep\/det300","article-title":"Time-lapse parameters as predictors of blastocyst development and pregnancy outcome in embryos from good prognosis patients: a prospective cohort study","volume":"28","author":"Kirkegaard","year":"2013","journal-title":"Hum. Reprod."},{"key":"10.1016\/j.rbmo.2024.104493_bib0016","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1016\/j.rbmo.2019.05.020","article-title":"Embryo morphokinetics is potentially associated with clinical outcomes of single-embryo transfers in preimplantation genetic testing for aneuploidy cycles","volume":"39","author":"Lee","year":"2019","journal-title":"Reprod. Biomed. Online"},{"key":"10.1016\/j.rbmo.2024.104493_bib0017","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1002\/mrd.22684","article-title":"Biological optimization, the Goldilocks principle, and how much is lagom in the preimplantation embryo","volume":"83","author":"Leese","year":"2016","journal-title":"Mol. Reprod. Dev."},{"key":"10.1016\/j.rbmo.2024.104493_bib0018","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/S1472-6483(10)60222-2","article-title":"Kinetic markers of human embryo quality using time-lapse recordings of IVF\/ICSI-fertilized oocytes","volume":"17","author":"Lemmen","year":"2008","journal-title":"Reprod. Biomed. Online"},{"key":"10.1016\/j.rbmo.2024.104493_bib0019","unstructured":"Li, K., Wang, Y., Gao, P., Song, G., Liu, Y., Li, H., Qiao, Y., 2022. UniFormer: Unified Transformer for Efficient Spatiotemporal Representation Learning. arXiv [cs.CV]. https:\/\/doi.org\/10.48550\/arXiv.2201.04676"},{"key":"10.1016\/j.rbmo.2024.104493_bib0020","doi-asserted-by":"crossref","first-page":"122153","DOI":"10.1109\/ACCESS.2019.2937765","article-title":"Multi-task deep learning with dynamic programming for embryo early development stage classification from time-lapse videos","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.rbmo.2024.104493_bib0021","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1095\/biolreprod.111.096602","article-title":"Loss of genomic imprinting in mouse embryos with fast rates of preimplantation development in culture","volume":"86","author":"Market Velker","year":"2012","journal-title":"Biol. Reprod."},{"key":"10.1016\/j.rbmo.2024.104493_bib0022","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0183328","article-title":"Inter-laboratory agreement on embryo classification and clinical decision: Conventional morphological assessment vs. time lapse","volume":"12","author":"Mart\u00ednez-Granados","year":"2017","journal-title":"PLoS One"},{"key":"10.1016\/j.rbmo.2024.104493_bib0023","doi-asserted-by":"crossref","first-page":"2658","DOI":"10.1093\/humrep\/der256","article-title":"The use of morphokinetics as a predictor of embryo implantation","volume":"26","author":"Meseguer","year":"2011","journal-title":"Hum. Reprod."},{"key":"10.1016\/j.rbmo.2024.104493_bib0024","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.advms.2017.02.001","article-title":"How much information about embryo implantation potential is included in morphokinetic data? A prediction model based on artificial neural networks and principal component analysis","volume":"62","author":"Milewski","year":"2017","journal-title":"Adv. Med. Sci."},{"key":"10.1016\/j.rbmo.2024.104493_bib0025","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/j.fertnstert.2015.11.001","article-title":"Morphokinetic analysis and embryonic prediction for blastocyst formation through an integrated time-lapse system","volume":"105","author":"Motato","year":"2016","journal-title":"Fertil. Steril."},{"key":"10.1016\/j.rbmo.2024.104493_bib0026","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.fertnstert.2018.01.042","article-title":"Time-lapse imaging: clearly useful to both laboratory personnel and patient outcomes versus just because we can doesn\u2019t mean we should","volume":"109","author":"Paulson","year":"2018","journal-title":"Fertil. Steril."},{"key":"10.1016\/j.rbmo.2024.104493_bib0027","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1016\/j.fertnstert.2014.07.738","article-title":"Clinical validation of embryo culture and selection by morphokinetic analysis: a randomized, controlled trial of the EmbryoScope","volume":"102","author":"Rubio","year":"2014","journal-title":"Fertil. Steril."},{"key":"10.1016\/j.rbmo.2024.104493_bib0028","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0242377","article-title":"Time-lapse imaging derived morphokinetic variables reveal association with implantation and live birth following in vitro fertilization: a retrospective study using data from transferred human embryos","volume":"15","author":"Sayed","year":"2020","journal-title":"PLoS One"},{"key":"10.1016\/j.rbmo.2024.104493_bib0029","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.fertnstert.2011.05.050","article-title":"Evidence of impaired endometrial receptivity after ovarian stimulation for in vitro fertilization: a prospective randomized trial comparing fresh and frozen-thawed embryo transfer in normal responders","volume":"96","author":"Shapiro","year":"2011","journal-title":"Fertil. Steril."},{"key":"10.1016\/j.rbmo.2024.104493_bib0030","series-title":"Nordic Artificial Intelligence Research and Development","first-page":"81","article-title":"Detecting Human Embryo Cleavage Stages Using YOLO V5 Object Detection Algorithm","author":"Sharma","year":"2022"},{"key":"10.1016\/j.rbmo.2024.104493_bib0031","doi-asserted-by":"crossref","first-page":"2103","DOI":"10.1093\/humrep\/deh385","article-title":"Early cleavage is a valuable addition to existing embryo selection parameters: a study using single embryo transfers","volume":"19","author":"Van Montfoort","year":"2004","journal-title":"Hum. Reprod."},{"key":"10.1016\/j.rbmo.2024.104493_bib0032","doi-asserted-by":"crossref","first-page":"1115","DOI":"10.1038\/nbt.1686","article-title":"Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage","volume":"28","author":"Wong","year":"2010","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.rbmo.2024.104493_bib0033","first-page":"116","article-title":"Development of a dynamic machine learning algorithm to predict clinical pregnancy and live birth rate with embryo morphokinetics","volume":"3","author":"Yang","year":"2022","journal-title":"Field Staff Rep"},{"key":"10.1016\/j.rbmo.2024.104493_bib0034","doi-asserted-by":"crossref","DOI":"10.1093\/humrep\/deac104.007","article-title":"O-007 Simplifying the complexity of time-lapse decisions with AI: CHLOE (Fairtility) can automatically annotate morphokinetics and predict blastulation (at 30hpi), pregnancy and ongoing clinical pregnancy","volume":"37","author":"Yelke","year":"2022","journal-title":"Hum. Reprod."}],"container-title":["Reproductive BioMedicine Online"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1472648324006825?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1472648324006825?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T20:24:06Z","timestamp":1762547046000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1472648324006825"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["S1472648324006825"],"URL":"https:\/\/doi.org\/10.1016\/j.rbmo.2024.104493","relation":{},"ISSN":["1472-6483"],"issn-type":[{"value":"1472-6483","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Association between embryo development and early pregnancy loss revealed by artificial-intelligence-annotated kinetic events","name":"articletitle","label":"Article Title"},{"value":"Reproductive BioMedicine Online","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.rbmo.2024.104493","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 The Author(s). Published by Elsevier Ltd on behalf of Reproductive Healthcare Ltd.","name":"copyright","label":"Copyright"}],"article-number":"104493"}}