{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T04:02:23Z","timestamp":1793764943544,"version":"4.6.1"},"reference-count":33,"publisher":"Elsevier BV","issue":"1","license":[{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T00:00:00Z","timestamp":1708646400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001171","name":"Cancer Institute NSW","doi-asserted-by":"publisher","award":["2021\/CDF1148"],"award-info":[{"award-number":["2021\/CDF1148"]}],"id":[{"id":"10.13039\/501100001171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001775","name":"University of Technology Sydney","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001775","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":[[2024,7]]},"DOI":"10.1016\/j.rbmo.2024.103910","type":"journal-article","created":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T14:58:40Z","timestamp":1708613920000},"page":"103910","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":32,"title":["Evaluation of an artificial intelligence-facilitated sperm detection tool in azoospermic samples for use in ICSI"],"prefix":"10.1016","volume":"49","author":[{"given":"Dale M.","family":"Goss","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven A.","family":"Vasilescu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phillip A.","family":"Vasilescu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Cooke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shannon HK.","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gavin P.","family":"Sacks","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David K.","family":"Gardner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Majid E.","family":"Warkiani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.rbmo.2024.103910_bib0001","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12958-015-0032-1","article-title":"A unique view on male infertility around the globe","volume":"13","author":"Agarwal","year":"2015","journal-title":"Reproductive biology and endocrinology"},{"key":"10.1016\/j.rbmo.2024.103910_bib0002","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13643-019-0942-7","article-title":"Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error","volume":"8","author":"Bannach-Brown","year":"2019","journal-title":"Systematic reviews"},{"key":"10.1016\/j.rbmo.2024.103910_bib0003","doi-asserted-by":"crossref","first-page":"e28","DOI":"10.1016\/S2589-7500(22)00213-8","article-title":"A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: A retrospective model development and validation study","volume":"5","author":"Barnes","year":"2023","journal-title":"The Lancet Digital Health"},{"key":"10.1016\/j.rbmo.2024.103910_bib0004","doi-asserted-by":"crossref","first-page":"125","DOI":"10.3390\/info11020125","article-title":"Albumentations: fast and flexible image augmentations","volume":"11","author":"Buslaev","year":"2020","journal-title":"Information"},{"key":"10.1016\/j.rbmo.2024.103910_bib0005","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1016\/j.rbmo.2020.07.003","article-title":"Embryo Ranking Intelligent Classification Algorithm (ERICA): artificial intelligence clinical assistant predicting embryo ploidy and implantation","volume":"41","author":"Chavez-Badiola","year":"2020","journal-title":"Reproductive BioMedicine Online"},{"key":"10.1016\/j.rbmo.2024.103910_bib0006","doi-asserted-by":"crossref","unstructured":"Cubuk E.D., Zoph B., Mane D., Vasudevan V., Le Q.V., 2018. Autoaugment: Learning augmentation policies from data. arXiv preprint arXiv:1805.09501.","DOI":"10.1109\/CVPR.2019.00020"},{"key":"10.1016\/j.rbmo.2024.103910_bib0007","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1111\/j.2047-2927.2013.00148.x","article-title":"Outcome of microdissection TESE compared with conventional TESE in non-obstructive azoospermia: a systematic review","volume":"2","author":"Deruyver","year":"2014","journal-title":"Androl"},{"key":"10.1016\/j.rbmo.2024.103910_bib0008","doi-asserted-by":"crossref","first-page":"1746","DOI":"10.1093\/humrep\/deac131","article-title":"Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF","volume":"37","author":"Diakiw","year":"2022","journal-title":"Human Reproduction"},{"key":"10.1016\/j.rbmo.2024.103910_bib0009","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":"Human Reproduction"},{"key":"10.1016\/j.rbmo.2024.103910_bib0010","doi-asserted-by":"crossref","first-page":"745","DOI":"10.21037\/tau.2017.07.07","article-title":"Microdissection testicular sperm extraction","volume":"6","author":"Flannigan","year":"2017","journal-title":"Translational Androl. and Urology."},{"key":"10.1016\/j.rbmo.2024.103910_bib0011","doi-asserted-by":"crossref","DOI":"10.1093\/humrep\/dead093.163","article-title":"O-136 Artificial intelligence to assist in surgical sperm detection and isolation","volume":"38","author":"Goss","year":"2023","journal-title":"Hum. Reproduction."},{"key":"10.1016\/j.rbmo.2024.103910_bib0012","doi-asserted-by":"crossref","first-page":"e38","DOI":"10.1016\/j.fertnstert.2019.07.230","article-title":"Artificial intelligence assessment of time-lapse images can predict with 77% accuracy whether a human embryo capable of achieving a pregnancy will miscarry","volume":"112","author":"Hariharan","year":"2019","journal-title":"Fertility and Steril."},{"key":"10.1016\/j.rbmo.2024.103910_bib0013","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/S0022-5347(17)38662-7","article-title":"Evaluation of the azoospermic patient","volume":"142","author":"Jarow","year":"1989","journal-title":"The J. of Urology."},{"key":"10.1016\/j.rbmo.2024.103910_bib0014","unstructured":"Jocher G., Chaurasia A., Qiu J. YOLO by Ultralytics. 2023. Ultralytics, GitHub."},{"key":"10.1016\/j.rbmo.2024.103910_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.rbmo.2023.103329","article-title":"A proof-of-concept prospective study of applying artificial intelligence for sperm selection in the IVF laboratory","author":"Joshi","year":"2023","journal-title":"Reproductive BioMedicine Online"},{"key":"10.1016\/j.rbmo.2024.103910_bib0016","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1093\/humupd\/dmac035","article-title":"Temporal trends in sperm count: a systematic review and meta-regression analysis of samples collected globally in the 20th and 21st centuries. Hum","volume":"29","author":"Levine","year":"2023","journal-title":"Reproduction Update"},{"key":"10.1016\/j.rbmo.2024.103910_bib0017","doi-asserted-by":"crossref","first-page":"S206","DOI":"10.21037\/tau.2019.08.36","article-title":"Towards a better testicular sperm extraction: novel sperm sorting technologies for non-motile sperm extracted by microdissection TESE","volume":"9","author":"Mangum","year":"2020","journal-title":"Translational Androl. and Urology."},{"key":"10.1016\/j.rbmo.2024.103910_bib0018","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1038\/s42003-019-0491-6","article-title":"Deep learning-based selection of human sperm with high DNA integrity","volume":"2","author":"McCallum","year":"2019","journal-title":"Communications Biology"},{"key":"10.1016\/j.rbmo.2024.103910_bib0019","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1016\/j.rbmo.2022.03.036","article-title":"Computer software (SiD) assisted real-time single sperm selection associated with fertilization and blastocyst formation","volume":"45","author":"Mendizabal-Ruiz","year":"2022","journal-title":"Reproductive BioMedicine Online"},{"key":"10.1016\/j.rbmo.2024.103910_bib0020","article-title":"The Effect of Different Timing after Ejaculation on Sperm Motility and Viability in Semen Analysis at Room Temperature","volume":"101","author":"Ouitrakul","year":"2018","journal-title":"J. of the M\u00e9d Association of Thail."},{"key":"10.1016\/j.rbmo.2024.103910_bib0021","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.fertnstert.2011.05.033","article-title":"Role of tissue digestion and extensive sperm search after microdissection testicular sperm extraction","volume":"96","author":"Ramasamy","year":"2011","journal-title":"Fertil. and Steril."},{"key":"10.1016\/j.rbmo.2024.103910_bib0022","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.1016\/j.urology.2004.12.059","article-title":"Structural and functional changes to the testis after conventional versus microdissection testicular sperm extraction","volume":"65","author":"Ramasamy","year":"2005","journal-title":"Urology"},{"key":"10.1016\/j.rbmo.2024.103910_bib0023","doi-asserted-by":"crossref","first-page":"161","DOI":"10.3109\/19396368.2016.1159748","article-title":"Microfluidics: The future of microdissection TESE?","volume":"62","author":"Samuel","year":"2016","journal-title":"Systems Biology in Reproductive Medicine"},{"key":"10.1016\/j.rbmo.2024.103910_bib0024","doi-asserted-by":"crossref","first-page":"6263","DOI":"10.1210\/jc.2004-2322","article-title":"Success of testicular sperm injection and intracytoplasmic sperm injection in men with Klinefelter syndrome","volume":"90","author":"Schiff","year":"2005","journal-title":"The J. of Clinical Endocrinology & Metabolism."},{"key":"10.1016\/j.rbmo.2024.103910_bib0025","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.1016\/S0022-5347(05)65676-5","article-title":"Need for sperm retrieval and cryopreservation at vasectomy reversal. The J","volume":"166","author":"Schrepferman","year":"2001","journal-title":"of Urology"},{"key":"10.1016\/j.rbmo.2024.103910_bib0026","doi-asserted-by":"crossref","first-page":"e430","DOI":"10.1016\/j.fertnstert.2018.08.034","article-title":"Artificial intelligence as a novel approach for embryo selection","volume":"110","author":"Tran","year":"2018","journal-title":"Fertil. and Steril."},{"key":"10.1016\/j.rbmo.2024.103910_bib0027","doi-asserted-by":"crossref","unstructured":"Tremblay J., Prakash A., Acuna D., Brophy M., Jampani V., Anil C., To T., Cameracci E., Boochoon S., Birchfield S. Training deep networks with synthetic data: Bridging the reality gap by domain randomization Proceedings of the IEEE conference on computer vision and pattern recognition workshops. 2018, pp. 969-977.","DOI":"10.1109\/CVPRW.2018.00143"},{"key":"10.1016\/j.rbmo.2024.103910_bib0028","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0224365","article-title":"Machine learning algorithm validation with a limited sample size","volume":"14","author":"Vabalas","year":"2019","journal-title":"PloS one"},{"key":"10.1016\/j.rbmo.2024.103910_bib0029","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12610-017-0050-2","article-title":"Processing and selection of surgically-retrieved sperm for ICSI: a review","volume":"27","author":"Verheyen","year":"2017","journal-title":"Basic and Clinical Androl."},{"key":"10.1016\/j.rbmo.2024.103910_bib0030","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1093\/humrep\/deaa013","article-title":"Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF","volume":"35","author":"VerMilyea","year":"2020","journal-title":"Hum. Reproduction."},{"key":"10.1016\/j.rbmo.2024.103910_bib0031","article-title":"Prediction of DNA integrity from morphological parameters using a single-sperm DNA fragmentation index assay","volume":"6","author":"Wang","year":"2019","journal-title":"Advanced Science"},{"key":"10.1016\/j.rbmo.2024.103910_bib0032","series-title":"Laboratory manual for the examination and processing of human semen","year":"2021"},{"key":"10.1016\/j.rbmo.2024.103910_bib0033","doi-asserted-by":"crossref","first-page":"e28218","DOI":"10.4161\/spmg.28218","article-title":"Review of azoospermia","volume":"4","author":"Wosnitzer","year":"2014","journal-title":"Spermatogenesis."}],"updated-by":[{"DOI":"10.1016\/j.rbmo.2025.105276","type":"erratum","label":"Erratum","source":"publisher","updated":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000}}],"container-title":["Reproductive BioMedicine Online"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1472648324000993?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1472648324000993?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T05:22:37Z","timestamp":1758950557000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1472648324000993"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,7]]}},"alternative-id":["S1472648324000993"],"URL":"https:\/\/doi.org\/10.1016\/j.rbmo.2024.103910","relation":{},"ISSN":["1472-6483"],"issn-type":[{"value":"1472-6483","type":"print"}],"subject":[],"published":{"date-parts":[[2024,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Evaluation of an artificial intelligence-facilitated sperm detection tool in azoospermic samples for use in ICSI","name":"articletitle","label":"Article Title"},{"value":"Reproductive BioMedicine Online","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.rbmo.2024.103910","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 The Authors. Published by Elsevier Ltd on behalf of Reproductive Healthcare Ltd.","name":"copyright","label":"Copyright"}],"article-number":"103910"}}