{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T02:38:56Z","timestamp":1783823936934,"version":"3.55.0"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2022,5,4]],"date-time":"2022-05-04T00:00:00Z","timestamp":1651622400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,5,4]],"date-time":"2022-05-04T00:00:00Z","timestamp":1651622400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1007\/s11517-022-02569-1","type":"journal-article","created":{"date-parts":[[2022,5,4]],"date-time":"2022-05-04T21:02:52Z","timestamp":1651698172000},"page":"1851-1861","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Predicting in vitro fertilization success in the Brazilian public health system: a machine learning approach"],"prefix":"10.1007","volume":"60","author":[{"given":"Nayara","family":"C. N. Barreto","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulia Z.","family":"Castro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramon G.","family":"Pereira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francisco A. N.","family":"Pereira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fernando M.","family":"Reis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wagner M.","family":"Junior","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ines K. D.","family":"Cavallo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6870-2063","authenticated-orcid":false,"given":"Karina B.","family":"Gomes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,5,4]]},"reference":[{"issue":"11","key":"2569_CR1","doi-asserted-by":"publisher","first-page":"2683","DOI":"10.1093\/humrep\/dep343","volume":"24","author":"F Zegers-Hochschild","year":"2009","unstructured":"Zegers-Hochschild F et al (2009) The International Committee for Monitoring Assisted Reproductive Technology (ICMART) and the World Health Organization (WHO) revised glossary on ART terminology, 2009. Hum Reprod 24(11):2683\u20132687","journal-title":"Hum Reprod"},{"issue":"4","key":"2569_CR2","doi-asserted-by":"publisher","first-page":"191","DOI":"10.4103\/0974-1208.170370","volume":"8","author":"N Kumar","year":"2015","unstructured":"Kumar N, Singh AK (2015) Trends of male factor infertility, an important cause of infertility: a review of literature. Journal of Human Reproductive Sciences 8(4):191","journal-title":"Journal of Human Reproductive Sciences"},{"issue":"7","key":"2569_CR3","doi-asserted-by":"publisher","first-page":"1454","DOI":"10.1093\/humrep\/12.7.1454","volume":"12","author":"S Kaufmann","year":"1997","unstructured":"Kaufmann S, Eastaugh J, Snowden S, Smye S, Sharma V (1997) The application of neural networks in predicting the outcome of in-vitro fertilization. Human Reproduction (Oxford, England) 12(7):1454\u20131457","journal-title":"Human Reproduction (Oxford, England)"},{"key":"2569_CR4","unstructured":"Ramasamy, N. et\u00a0al. Feature reduction by improvised hybrid algorithm for predicting the IVF success rate. International Journal of Advanced Research in Computer Science 8\u00a0(1) (2017)"},{"issue":"7","key":"2569_CR5","doi-asserted-by":"publisher","first-page":"2283","DOI":"10.1007\/s00521-018-3693-9","volume":"32","author":"MR Hassan","year":"2020","unstructured":"Hassan MR, Al-Insaif S, Hossain MI, Kamruzzaman J (2020) A machine learning approach for prediction of pregnancy outcome following IVF treatment. Neural Comput Appl 32(7):2283\u20132297","journal-title":"Neural Comput Appl"},{"issue":"3","key":"2569_CR6","first-page":"184","volume":"11","author":"P Hafiz","year":"2017","unstructured":"Hafiz P, Nematollahi M, Boostani R, Jahromi BN (2017) Predicting implantation outcome of in vitro fertilization and intracytoplasmic sperm injection using data mining techniques. International journal of fertility & sterility 11(3):184","journal-title":"International journal of fertility & sterility"},{"issue":"2","key":"2569_CR7","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1016\/j.fertnstert.2018.10.030","volume":"111","author":"C Blank","year":"2019","unstructured":"Blank C et al (2019) Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective. Fertil Steril 111(2):318\u2013326","journal-title":"Fertil Steril"},{"issue":"1","key":"2569_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41746-019-0096-y","volume":"2","author":"P Khosravi","year":"2019","unstructured":"Khosravi P et al (2019) Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization. NPJ Digital Medicine 2(1):1\u20139","journal-title":"NPJ Digital Medicine"},{"issue":"4","key":"2569_CR9","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1007\/s10815-019-01408-x","volume":"36","author":"CL Curchoe","year":"2019","unstructured":"Curchoe CL, Bormann CL (2019) Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018. J Assist Reprod Genet 36(4):591\u2013600","journal-title":"J Assist Reprod Genet"},{"issue":"4","key":"2569_CR10","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1093\/humupd\/dmv016","volume":"21","author":"MC Inhorn","year":"2015","unstructured":"Inhorn MC, Patrizio P (2015) Infertility around the globe: new thinking on gender, reproductive technologies and global movements in the 21st century. Hum Reprod Update 21(4):411\u2013426","journal-title":"Hum Reprod Update"},{"issue":"13","key":"2569_CR11","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 (2018) Big data and machine learning in health care. JAMA 319(13):1317\u20131318","journal-title":"JAMA"},{"issue":"6","key":"2569_CR12","doi-asserted-by":"publisher","first-page":"714","DOI":"10.1177\/0272989X14535984","volume":"35","author":"A Uyar","year":"2015","unstructured":"Uyar A, Bener A, Ciray HN (2015) Predictive modeling of implantation outcome in an in vitro fertilization setting: an application of machine learning methods. Med Decis Making 35(6):714\u2013725","journal-title":"Med Decis Making"},{"issue":"2","key":"2569_CR13","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.jval.2014.12.005","volume":"18","author":"WH Crown","year":"2015","unstructured":"Crown WH (2015) Potential application of machine learning in health outcomes research and some statistical cautions. Value in Health 18(2):137\u2013140","journal-title":"Value in Health"},{"issue":"1","key":"2569_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12967-018-1762-6","volume":"17","author":"J Qiu","year":"2019","unstructured":"Qiu J, Li P, Dong M, Xin X, Tan J (2019) Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method. J Transl Med 17(1):1\u20138","journal-title":"J Transl Med"},{"key":"2569_CR15","unstructured":"Babitha, M. Survey on the machine learning techniques used in IVF treatment to improve the success rate (2019)"},{"issue":"16","key":"2569_CR16","doi-asserted-by":"publisher","first-page":"8761","DOI":"10.1021\/acs.jmedchem.9b01101","volume":"63","author":"R Rodr\u00edguez-P\u00e9rez","year":"2019","unstructured":"Rodr\u00edguez-P\u00e9rez R, Bajorath J (2019) Interpretation of compound activity predictions from complex machine learning models using local approximations and Shapley values. J Med Chem 63(16):8761\u20138777","journal-title":"J Med Chem"},{"issue":"11","key":"2569_CR17","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.4103\/0366-6999.232808","volume":"131","author":"Y-Y Zhao","year":"2018","unstructured":"Zhao Y-Y, Yu Y, Zhang X-W (2018) Overall blastocyst quality, trophectoderm grade, and inner cell mass grade predict pregnancy outcome in euploid blastocyst transfer cycles. Chin Med J 131(11):1261\u20131267","journal-title":"Chin Med J"},{"issue":"3","key":"2569_CR18","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.xfre.2020.09.003","volume":"1","author":"I Lai","year":"2020","unstructured":"Lai I et al (2020) Transfers of lower quality embryos based on morphological appearance result in appreciable live birth rates: a Canadian center\u2019s experience. F&S Reports 1(3):264\u2013269","journal-title":"F&S Reports"},{"key":"2569_CR19","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.rse.2013.10.026","volume":"141","author":"M K\u00fchnlein","year":"2014","unstructured":"K\u00fchnlein M, Appelhans T, Thies B, Nauss T (2014) Improving the accuracy of rainfall rates from optical satellite sensors with machine learning-a random forests-based approach applied to MSG SEVIRI. Remote Sens Environ 141:129\u2013143","journal-title":"Remote Sens Environ"},{"issue":"1","key":"2569_CR20","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1016\/S1472-6483(10)62193-1","volume":"2","author":"S Brugo-Olmedo","year":"2001","unstructured":"Brugo-Olmedo S, Chillik C, Kopelman S (2001) Definition and causes of infertility. Reprod Biomed Online 2(1):173\u2013185","journal-title":"Reprod Biomed Online"},{"key":"2569_CR21","first-page":"1","volume":"64","author":"E Brandy","year":"2015","unstructured":"Brandy E et al (2015) Births: final data for 2014. Nat Vital Stat Rep 64:1\u201364","journal-title":"Nat Vital Stat Rep"},{"issue":"4","key":"2569_CR22","doi-asserted-by":"publisher","first-page":"901","DOI":"10.1067\/S0002-9378(03)00753-1","volume":"189","author":"E De la Rochebrochard","year":"2003","unstructured":"De la Rochebrochard E, Thonneau P (2003) Paternal age $$\\ge$$ 40 years: an important risk factor for infertility. Am J Obstet Gynecol 189(4):901\u2013905","journal-title":"Am J Obstet Gynecol"},{"issue":"3","key":"2569_CR23","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1007\/s00404-016-4136-4","volume":"294","author":"AC Rossi","year":"2016","unstructured":"Rossi AC, Prefumo F (2016) The effects of surgery for endometriosis on pregnancy outcomes following in vitro fertilization and embryo transfer: a systematic review and meta-analysis. Arch Gynecol Obstet 294(3):647\u2013655","journal-title":"Arch Gynecol Obstet"},{"issue":"8","key":"2569_CR24","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1007\/s10815-018-1214-5","volume":"35","author":"M Murta","year":"2018","unstructured":"Murta M et al (2018) Endometriosis does not affect live birth rates of patients submitted to assisted reproduction techniques: analysis of the Latin American network registry database from 1995 to 2011. J Assist Reprod Genet 35(8):1395\u20131399","journal-title":"J Assist Reprod Genet"},{"issue":"1","key":"2569_CR25","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.rbmo.2018.09.014","volume":"38","author":"S Sharma","year":"2019","unstructured":"Sharma S et al (2019) Does presence of adenomyosis affect reproductive outcome in IVF cycles? A retrospective analysis of 973 patients. Reprod Biomed Online 38(1):13\u201321","journal-title":"Reprod Biomed Online"},{"issue":"4","key":"2569_CR26","doi-asserted-by":"publisher","first-page":"1043","DOI":"10.1093\/humrep\/des012","volume":"27","author":"M Ballester","year":"2012","unstructured":"Ballester M et al (2012) Cumulative pregnancy rate after ICSI-IVF in patients with colorectal endometriosis: results of a multicentre study. Hum Reprod 27(4):1043\u20131049","journal-title":"Hum Reprod"},{"issue":"5","key":"2569_CR27","doi-asserted-by":"publisher","first-page":"1236","DOI":"10.1016\/j.fertnstert.2015.01.032","volume":"103","author":"S Ferrero","year":"2015","unstructured":"Ferrero S et al (2015) Second surgery for recurrent unilateral endometriomas and impact on ovarian reserve: a case-control study. Fertil Steril 103(5):1236\u20131243","journal-title":"Fertil Steril"},{"issue":"3","key":"2569_CR28","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1016\/j.ajog.2016.11.1042","volume":"216","author":"C Maignien","year":"2017","unstructured":"Maignien C et al (2017) Prognostic factors for assisted reproductive technology in women with endometriosis-related infertility. Am J Obstet Gynecol 216(3):280-e1","journal-title":"Am J Obstet Gynecol"},{"issue":"3","key":"2569_CR29","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1016\/j.fertnstert.2016.12.005","volume":"107","author":"KK Vaegter","year":"2017","unstructured":"Vaegter KK et al (2017) Which factors are most predictive for live birth after in vitro fertilization and intracytoplasmic sperm injection (IVF\/ICSI) treatments? Analysis of 100 prospectively recorded variables in 8,400 IVF\/ICSI single-embryo transfers. Fertil Steril 107(3):641\u2013648","journal-title":"Fertil Steril"},{"issue":"12","key":"2569_CR30","doi-asserted-by":"publisher","first-page":"997","DOI":"10.3109\/09513590.2011.579654","volume":"27","author":"SA Choe","year":"2011","unstructured":"Choe SA et al (2011) Symmetry in number of retrieved oocytes between two ovaries: a possible predictor of in vitro fertilization outcome. Gynecol Endocrinol 27(12):997\u20131000","journal-title":"Gynecol Endocrinol"},{"issue":"7","key":"2569_CR31","doi-asserted-by":"publisher","first-page":"1768","DOI":"10.1093\/humrep\/der106","volume":"26","author":"SK Sunkara","year":"2011","unstructured":"Sunkara SK et al (2011) Association between the number of eggs and live birth in IVF treatment: an analysis of 400 135 treatment cycles. Hum Reprod 26(7):1768\u20131774","journal-title":"Hum Reprod"},{"issue":"4","key":"2569_CR32","doi-asserted-by":"publisher","first-page":"967","DOI":"10.1016\/j.fertnstert.2013.12.026","volume":"101","author":"RG Steward","year":"2014","unstructured":"Steward RG et al (2014) Oocyte number as a predictor for ovarian hyperstimulation syndrome and live birth: an analysis of 256,381 in vitro fertilization cycles. Fertil Steril 101(4):967\u2013973","journal-title":"Fertil Steril"},{"key":"2569_CR33","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1100\/tsw.2006.145","volume":"6","author":"T Timeva","year":"2006","unstructured":"Timeva T et al (2006) Correlation between number of retrieved oocytes and pregnancy rate after in vitro fertilization\/intracytoplasmic sperm infection. Sci World J 6:686\u2013690","journal-title":"Sci World J"},{"issue":"1","key":"2569_CR34","first-page":"40","volume":"7","author":"M Bals-Pratsch","year":"2010","unstructured":"Bals-Pratsch M et al (2010) Extended analyses of the German IVF registry (DIR): andrological aspects, medical-economical assumptions related to the shift from IVF to ICSI and stimulation with gonadotropins. Journal f\u00fcr Reproduktionsmedizin und Endokrinologie-Journal of Reproductive Medicine and Endocrinology 7(1):40\u201344","journal-title":"Journal f\u00fcr Reproduktionsmedizin und Endokrinologie-Journal of Reproductive Medicine and Endocrinology"},{"issue":"2","key":"2569_CR35","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.rbmo.2014.10.013","volume":"30","author":"P Gambadauro","year":"2015","unstructured":"Gambadauro P, Navaratnarajah R (2015) Reporting of embryo transfer methods in IVF research: a cross-sectional study. Reprod Biomed Online 30(2):137\u2013143","journal-title":"Reprod Biomed Online"},{"key":"2569_CR36","doi-asserted-by":"crossref","unstructured":"Brown, J., Buckingham, K., Buckett, W. & Abou-Setta, A.\u00a0M. Ultrasound versus \u2019clinical touch\u2019 for catheter guidance during embryo transfer in women. Cochrane database of systematic reviews (3) (2016)","DOI":"10.1002\/14651858.CD006107.pub4"},{"issue":"5","key":"2569_CR37","first-page":"905","volume":"48","author":"X Ren","year":"2016","unstructured":"Ren X et al (2016) Effect of catheter choice during embryo transfer on the clinical outcome of in vitro fertilization-embryo transfer. Beijing da xue xue bao. Yi xue ban= Journal of Peking University. Health Sciences 48(5):905\u2013909","journal-title":"Beijing da xue xue bao. Yi xue ban= Journal of Peking University. Health Sciences"}],"container-title":["Medical & Biological Engineering & Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-022-02569-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-022-02569-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-022-02569-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,24]],"date-time":"2022-06-24T03:38:55Z","timestamp":1656041935000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-022-02569-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,4]]},"references-count":37,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["2569"],"URL":"https:\/\/doi.org\/10.1007\/s11517-022-02569-1","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,4]]},"assertion":[{"value":"15 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 March 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 May 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}