{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T04:04:07Z","timestamp":1792123447903,"version":"4.4.0"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T00:00:00Z","timestamp":1740355200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T00:00:00Z","timestamp":1740355200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100001466","name":"American Urological Association Foundation","doi-asserted-by":"publisher","award":["Rising Star"],"award-info":[{"award-number":["Rising Star"]}],"id":[{"id":"10.13039\/100001466","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000245","name":"Michael Smith Health Research BC","doi-asserted-by":"publisher","award":["Health Professional Investigator Grant"],"award-info":[{"award-number":["Health Professional Investigator Grant"]}],"id":[{"id":"10.13039\/501100000245","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Curr Urol Rep"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s11934-025-01257-5","type":"journal-article","created":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T05:06:41Z","timestamp":1740373601000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Artificial Intelligence in Andrology: A New Frontier in Male Infertility Diagnosis and Treatment"],"prefix":"10.1007","volume":"26","author":[{"given":"Joseph Y.","family":"Nashed","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kiera","family":"Liblik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Dergham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luke","family":"Witherspoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan","family":"Flannigan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,2,24]]},"reference":[{"key":"1257_CR1","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1016\/S0015-0282(02)03105-9","volume":"77","author":"ID Sharlip","year":"2002","unstructured":"Sharlip ID, Jarow JP, Belker AM, et al. Best practice policies for male infertility. Fertil Steril. 2002;77:873.","journal-title":"Fertil Steril"},{"key":"1257_CR2","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.clinbiochem.2018.03.012","volume":"62","author":"M Vander Borght","year":"2018","unstructured":"Vander Borght M, Wyns C. Fertility and infertility: definition and epidemiology. Clin Biochem. 2018;62:2.","journal-title":"Clin Biochem"},{"key":"1257_CR3","doi-asserted-by":"publisher","first-page":"357","DOI":"10.4103\/1008-682X.179252","volume":"18","author":"JD Ring","year":"2016","unstructured":"Ring JD, Lwin AA, Kohler TS. Current medical management of endocrine-related male infertility. Asian J Androl. 2016;18:357.","journal-title":"Asian J Androl"},{"key":"1257_CR4","doi-asserted-by":"crossref","unstructured":"Punjani N, Kang C, Lee RK et al. Technological advancements in male infertility microsurgery. J Clin Med. 2021;10.","DOI":"10.3390\/jcm10184259"},{"key":"1257_CR5","doi-asserted-by":"crossref","unstructured":"Virtanen HE, Jorgensen N, Toppari J. Semen quality in the 21(St) century. Nat Rev Urol. 2017;14:120.","DOI":"10.1038\/nrurol.2016.261"},{"key":"1257_CR6","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1093\/humupd\/dmac035","volume":"29","author":"H Levine","year":"2023","unstructured":"Levine H, Jorgensen N, Martino-Andrade A, et al. Temporal trends in sperm count: a systematic review and meta-regression analysis of samples collected globally in the 20th and 21st centuries. Hum Reprod Update. 2023;29:157.","journal-title":"Hum Reprod Update"},{"key":"1257_CR7","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1186\/s12958-015-0032-1","volume":"13","author":"A Agarwal","year":"2015","unstructured":"Agarwal A, Mulgund A, Hamada A, et al. A unique view on male infertility around the globe. Reprod Biol Endocrinol. 2015;13:37.","journal-title":"Reprod Biol Endocrinol"},{"key":"1257_CR8","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1093\/humupd\/dmp048","volume":"16","author":"TG Cooper","year":"2010","unstructured":"Cooper TG, Noonan E, von Eckardstein S, et al. World Health Organization reference values for human semen characteristics. Hum Reprod Update. 2010;16:231.","journal-title":"Hum Reprod Update"},{"key":"1257_CR9","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1016\/j.fertnstert.2021.12.012","volume":"117","author":"L Bjorndahl","year":"2022","unstructured":"Bjorndahl L, Kirkman Brown J, other Editorial Board Members of the, W. H. O. L. M. f. t. E. et al. The sixth edition of the WHO Laboratory Manual for the examination and Processing of Human Semen: ensuring quality and standardization in basic examination of human ejaculates. Fertil Steril. 2022;117:246.","journal-title":"Fertil Steril"},{"key":"1257_CR10","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.rbmo.2014.02.013","volume":"29","author":"A Agarwal","year":"2014","unstructured":"Agarwal A, Durairajanayagam D, Halabi J, et al. Proteomics, oxidative stress and male infertility. Reprod Biomed Online. 2014;29:32.","journal-title":"Reprod Biomed Online"},{"key":"1257_CR11","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1093\/oxfordjournals.humrep.a137150","volume":"5","author":"R Menkveld","year":"1990","unstructured":"Menkveld R, Stander FS, Kotze TJ, et al. The evaluation of morphological characteristics of human spermatozoa according to stricter criteria. Hum Reprod. 1990;5:586.","journal-title":"Hum Reprod"},{"key":"1257_CR12","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.ucl.2023.06.005","volume":"51","author":"R Abid","year":"2024","unstructured":"Abid R, Hussein AA, Guru KA. Artificial Intelligence in Urology: current status and future perspectives. Urol Clin North Am. 2024;51:117.","journal-title":"Urol Clin North Am"},{"key":"1257_CR13","doi-asserted-by":"publisher","first-page":"39","DOI":"10.5534\/wjmh.230050","volume":"42","author":"RA Ghayda","year":"2024","unstructured":"Ghayda RA, Cannarella R, Calogero AE, et al. Artificial Intelligence in Andrology: from Semen Analysis to Image Diagnostics. World J Mens Health. 2024;42:39.","journal-title":"World J Mens Health"},{"key":"1257_CR14","doi-asserted-by":"publisher","first-page":"2036","DOI":"10.1093\/humrep\/14.8.2036","volume":"14","author":"G Barroso","year":"1999","unstructured":"Barroso G, Mercan R, Ozgur K, et al. Intra- and inter-laboratory variability in the assessment of sperm morphology by strict criteria: impact of semen preparation, staining techniques and manual versus computerized analysis. Hum Reprod. 1999;14:2036.","journal-title":"Hum Reprod"},{"key":"1257_CR15","doi-asserted-by":"publisher","first-page":"1018","DOI":"10.1093\/humrep\/deg197","volume":"18","author":"F Eustache","year":"2003","unstructured":"Eustache F, Auger J. Inter-individual variability in the morphological assessment of human sperm: effect of the level of experience and the use of standard methods. Hum Reprod. 2003;18:1018.","journal-title":"Hum Reprod"},{"key":"1257_CR16","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1111\/andr.12389","volume":"5","author":"N Gatimel","year":"2017","unstructured":"Gatimel N, Moreau J, Parinaud J, et al. Sperm morphology: assessment, pathophysiology, clinical relevance, and state of the art in 2017. Andrology. 2017;5:845.","journal-title":"Andrology"},{"key":"1257_CR17","first-page":"639","volume":"81","author":"AM Rivera-Montes","year":"2013","unstructured":"Rivera-Montes AM, Rivera-Gallegos A, Rodriguez-Villasana E, et al. [Estimate of the variability in the evaluation of semen analysis]. Ginecol Obstet Mex. 2013;81:639.","journal-title":"Ginecol Obstet Mex"},{"key":"1257_CR18","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436.","journal-title":"Nature"},{"key":"1257_CR19","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.compbiomed.2017.03.029","volume":"84","author":"V Chang","year":"2017","unstructured":"Chang V, Heutte L, Petitjean C, et al. Automatic classification of human sperm head morphology. Comput Biol Med. 2017;84:205.","journal-title":"Comput Biol Med"},{"key":"1257_CR20","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1016\/j.compbiomed.2019.04.030","volume":"109","author":"S Javadi","year":"2019","unstructured":"Javadi S, Mirroshandel SA. A novel deep learning method for automatic assessment of human sperm images. Comput Biol Med. 2019;109:182.","journal-title":"Comput Biol Med"},{"key":"1257_CR21","doi-asserted-by":"publisher","first-page":"18302","DOI":"10.1073\/pnas.2001754117","volume":"117","author":"ME Kandel","year":"2020","unstructured":"Kandel ME, Rubessa M, He YR, et al. Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure. Proc Natl Acad Sci U S A. 2020;117:18302.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"1257_CR22","doi-asserted-by":"crossref","unstructured":"Liu G, Shi H, Zhang H et al. Fast Noninvasive Morphometric Characterization of Free Human Sperms Using Deep Learning. Microsc Microanal. 2022;1.","DOI":"10.1017\/S1431927622012132"},{"key":"1257_CR23","doi-asserted-by":"crossref","unstructured":"Tseng KK, Li Y, Hsu CY et al. Computer-assisted system with multiple feature fused support vector machine for sperm morphology diagnosis. Biomed Res Int. 2013;2013:687607.","DOI":"10.1155\/2013\/687607"},{"key":"1257_CR24","doi-asserted-by":"crossref","unstructured":"Mahali MI, Leu JS, Darmawan JT et al. A Dual Architecture Fusion and AutoEncoder for Automatic Morphological classification of human sperm. Sens (Basel). 2023;23.","DOI":"10.3390\/s23146613"},{"key":"1257_CR25","doi-asserted-by":"publisher","first-page":"515","DOI":"10.3390\/math11030515","volume":"11","author":"S Shahzad","year":"2023","unstructured":"Shahzad S, Ilyas M, Lali MIU, et al. Sperm abnormality detection using sequential deep neural network. Mathematics. 2023;11:515.","journal-title":"Mathematics"},{"key":"1257_CR26","doi-asserted-by":"publisher","first-page":"2200111","DOI":"10.1002\/aisy.202200111","volume":"4","author":"L Spencer","year":"2022","unstructured":"Spencer L, Fernando J, Akbaridoust F, et al. Ensembled Deep Learning for the classification of human sperm head morphology. Adv Intell Syst. 2022;4:2200111.","journal-title":"Adv Intell Syst"},{"key":"1257_CR27","doi-asserted-by":"publisher","first-page":"e20031","DOI":"10.2196\/20031","volume":"8","author":"VF Tsai","year":"2020","unstructured":"Tsai VF, Zhuang B, Pong YH, et al. Web- and Artificial Intelligence-Based Image Recognition for Sperm Motility Analysis: Verification Study. JMIR Med Inf. 2020;8:e20031.","journal-title":"JMIR Med Inf"},{"key":"1257_CR28","doi-asserted-by":"crossref","unstructured":"Kanakasabapathy MK, Sadasivam M, Singh A et al. An automated smartphone-based diagnostic assay for point-of-care semen analysis. Sci Transl Med. 2017;9.","DOI":"10.1126\/scitranslmed.aai7863"},{"key":"1257_CR29","doi-asserted-by":"publisher","first-page":"380","DOI":"10.4111\/icu.2019.60.5.380","volume":"60","author":"WH Cheon","year":"2019","unstructured":"Cheon WH, Park HJ, Park MJ, et al. Validation of a smartphone-based, computer-assisted sperm analysis system compared with laboratory-based manual microscopic semen analysis and computer-assisted semen analysis. Investig Clin Urol. 2019;60:380.","journal-title":"Investig Clin Urol"},{"key":"1257_CR30","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1093\/biolre\/iox120","volume":"97","author":"SG Goodson","year":"2017","unstructured":"Goodson SG, White S, Stevans AM, et al. CASAnova: a multiclass support vector machine model for the classification of human sperm motility patterns. Biol Reprod. 2017;97:698.","journal-title":"Biol Reprod"},{"key":"1257_CR31","doi-asserted-by":"crossref","unstructured":"Serrano Berenguer L, Hincapi\u00e9 Monsalve S, Lara Cerrillo S et al. P-101\u2003machine and deep learning models to classify Comet assay tests for sperm DNA fragmentation evaluation. Hum Reprod. 2022;37.","DOI":"10.1093\/humrep\/deac107.097"},{"key":"1257_CR32","doi-asserted-by":"publisher","first-page":"16","DOI":"10.4103\/jhrs.jhrs_4_23","volume":"16","author":"RS Kumar","year":"2023","unstructured":"Kumar RS, Sharma S, Halder A, et al. Deep learning-based robust Automated System for Predicting Human sperm DNA fragmentation index. J Hum Reprod Sci. 2023;16:16.","journal-title":"J Hum Reprod Sci"},{"key":"1257_CR33","doi-asserted-by":"publisher","first-page":"618","DOI":"10.5534\/wjmh.210159","volume":"40","author":"J Ory","year":"2022","unstructured":"Ory J, Tradewell MB, Blankstein U, et al. Artificial Intelligence Based Machine Learning models predict sperm parameter upgrading after Varicocele Repair: a multi-institutional analysis. World J Mens Health. 2022;40:618.","journal-title":"World J Mens Health"},{"key":"1257_CR34","doi-asserted-by":"publisher","first-page":"e12454","DOI":"10.1002\/rmb2.12454","volume":"21","author":"T Sato","year":"2022","unstructured":"Sato T, Kishi H, Murakata S, et al. A new deep-learning model using YOLOv3 to support sperm selection during intracytoplasmic sperm injection procedure. Reprod Med Biol. 2022;21:e12454.","journal-title":"Reprod Med Biol"},{"key":"1257_CR35","doi-asserted-by":"publisher","first-page":"105918","DOI":"10.1016\/j.cmpb.2020.105918","volume":"200","author":"D Somasundaram","year":"2021","unstructured":"Somasundaram D, Nirmala M. Faster region convolutional neural network and semen tracking algorithm for sperm analysis. Comput Methods Programs Biomed. 2021;200:105918.","journal-title":"Comput Methods Programs Biomed"},{"key":"1257_CR36","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1016\/j.rbmo.2022.03.036","volume":"45","author":"G Mendizabal-Ruiz","year":"2022","unstructured":"Mendizabal-Ruiz G, Chavez-Badiola A, Figueroa A. Computer software (SiD) assisted real-time single sperm selection associated with fertilization and blastocyst formation. Reprod Biomed Online. 2022;45:703.","journal-title":"Reprod Biomed Online"},{"key":"1257_CR37","doi-asserted-by":"crossref","unstructured":"Valiu\u0161kait\u0117 V, Raudonis V, Maskeli\u016bnas R et al. Deep learning based evaluation of Spermatozoid Motility for Artificial Insemination. Sens (Basel). 2020;21.","DOI":"10.3390\/s21010072"},{"key":"1257_CR38","doi-asserted-by":"publisher","first-page":"28551","DOI":"10.1007\/s11042-020-09396-2","volume":"79","author":"WC Tan","year":"2020","unstructured":"Tan WC, Isa M, Mohamed NA. Automated human sperm tracking using mean shift - collision detection and modified covariance matrix method. Multimedia Tools Appl. 2020;79:28551.","journal-title":"Multimedia Tools Appl"},{"key":"1257_CR39","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1088\/0967-3334\/26\/5\/006","volume":"26","author":"VR Nafisi","year":"2005","unstructured":"Nafisi VR, Moradi MH, Nasr-Esfahani MH. A template matching algorithm for sperm tracking and classification. Physiol Meas. 2005;26:639.","journal-title":"Physiol Meas"},{"key":"1257_CR40","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.fertnstert.2022.03.011","volume":"118","author":"R Lee","year":"2022","unstructured":"Lee R, Witherspoon L, Robinson M, et al. Automated rare sperm identification from low-magnification microscopy images of dissociated microsurgical testicular sperm extraction samples using deep learning. Fertil Steril. 2022;118:90.","journal-title":"Fertil Steril"},{"key":"1257_CR41","doi-asserted-by":"crossref","unstructured":"Kobayashi H, Uetani M, Yamabe F et al. AI Model Developed Using Machine Learning for Predicting Sperm Retrieval in Micro-TESE for Nonobstructive Azoospermia Patients. Andrologia. 2023;2013:5693116.","DOI":"10.1155\/2023\/5693116"},{"key":"1257_CR42","first-page":"480","volume":"96","author":"H Kiuchi","year":"2005","unstructured":"Kiuchi H, Koga M, Hirai T, et al. Predictive factors associated with successful varicocele repair a study of 139 infertile men with valicocele. Nihon Hinyokika Gakkai Zasshi. 2005;96:480.","journal-title":"Nihon Hinyokika Gakkai Zasshi"},{"key":"1257_CR43","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1001\/jama.2017.18391","volume":"319","author":"AL Beam","year":"2018","unstructured":"Beam AL, Kohane IS. Big Data and Machine Learning in Health Care. JAMA. 2018;319:1317.","journal-title":"JAMA"},{"key":"1257_CR44","doi-asserted-by":"publisher","first-page":"2377","DOI":"10.1001\/jama.2019.18058","volume":"322","author":"RB Parikh","year":"2019","unstructured":"Parikh RB, Teeple S, Navathe AS. Addressing bias in artificial intelligence in health care. JAMA. 2019;322:2377.","journal-title":"JAMA"},{"key":"1257_CR45","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1016\/j.ogc.2023.09.003","volume":"50","author":"VS Jiang","year":"2023","unstructured":"Jiang VS, Pavlovic ZJ, Hariton E. The role of Artificial Intelligence and Machine Learning in assisted Reproductive technologies. Obstet Gynecol Clin North Am. 2023;50:747.","journal-title":"Obstet Gynecol Clin North Am"},{"key":"1257_CR46","doi-asserted-by":"publisher","first-page":"7","DOI":"10.3389\/fpubh.2016.00007","volume":"4","author":"P Kostkova","year":"2016","unstructured":"Kostkova P, Brewer H, de Lusignan S, et al. Who owns the data? Open Data for Healthcare. Front Public Health. 2016;4:7.","journal-title":"Front Public Health"}],"container-title":["Current Urology Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11934-025-01257-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11934-025-01257-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11934-025-01257-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T19:04:08Z","timestamp":1767985448000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11934-025-01257-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,24]]},"references-count":46,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["1257"],"URL":"https:\/\/doi.org\/10.1007\/s11934-025-01257-5","relation":{},"ISSN":["1527-2737","1534-6285"],"issn-type":[{"value":"1527-2737","type":"print"},{"value":"1534-6285","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,24]]},"assertion":[{"value":"1 February 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 February 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This article does not contain any studies with human or animal subjects performed by any of the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed Consent"}},{"value":"R.F. co-Founder of Teumo Health Technologies Inc.; received speaking honorarium from Ferring.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}],"article-number":"29"}}