{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T07:43:58Z","timestamp":1790927038407,"version":"4.1.0"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,2,16]],"date-time":"2025-02-16T00:00:00Z","timestamp":1739664000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,2,16]],"date-time":"2025-02-16T00:00:00Z","timestamp":1739664000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100005632","name":"Narodowe Centrum Bada\u0144 i Rozwoju","doi-asserted-by":"publisher","award":["POWR.03.02.00-00-I019\/16-00"],"award-info":[{"award-number":["POWR.03.02.00-00-I019\/16-00"]}],"id":[{"id":"10.13039\/501100005632","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005632","name":"Narodowe Centrum Bada\u0144 i Rozwoju","doi-asserted-by":"publisher","award":["POWR.03.02.00-00-I019\/16-00"],"award-info":[{"award-number":["POWR.03.02.00-00-I019\/16-00"]}],"id":[{"id":"10.13039\/501100005632","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-025-89905-1","type":"journal-article","created":{"date-parts":[[2025,2,16]],"date-time":"2025-02-16T11:42:02Z","timestamp":1739706122000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Predicting preterm birth using machine learning methods"],"prefix":"10.1038","volume":"15","author":[{"given":"Anna","family":"Kloska","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alicja","family":"Harmoza","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sylwester M.","family":"Kloska","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomasz","family":"Marciniak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iwona","family":"Sadowska-Krawczenko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,2,16]]},"reference":[{"key":"89905_CR1","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1891\/0730-0832.34.4.231","volume":"34","author":"LB Rubarth","year":"2015","unstructured":"Rubarth, L. B. & Quinn, J. Respiratory development and respiratory distress syndrome. Neonatal Netw. 34, 231\u2013238 (2015).","journal-title":"Neonatal Netw."},{"key":"89905_CR2","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1056\/NEJMra1005408","volume":"364","author":"J Neu","year":"2011","unstructured":"Neu, J. & Walker, W. A. Necrotizing enterocolitis. N. Engl. J. Med. 364, 255\u2013264 (2011).","journal-title":"N. Engl. J. Med."},{"key":"89905_CR3","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1203\/00006450-200111000-00003","volume":"50","author":"JJ Volpe","year":"2001","unstructured":"Volpe, J. J. Neurobiology of periventricular leukomalacia in the premature infant. Pediatr. Res. 50, 553\u2013562 (2001).","journal-title":"Pediatr. Res."},{"key":"89905_CR4","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/j.ophtha.2014.07.050","volume":"122","author":"ME Hartnett","year":"2015","unstructured":"Hartnett, M. E. Pathophysiology and mechanisms of severe retinopathy of prematurity. Ophthalmology 122, 200\u2013210 (2015).","journal-title":"Ophthalmology"},{"key":"89905_CR5","doi-asserted-by":"publisher","first-page":"1445","DOI":"10.1016\/S0140-6736(13)60178-6","volume":"382","author":"A Hellstr\u00f6m","year":"2013","unstructured":"Hellstr\u00f6m, A., Smith, L. E. & Dammann, O. Retinopathy of prematurity. Lancet 382, 1445\u20131457 (2013).","journal-title":"Lancet"},{"key":"89905_CR6","doi-asserted-by":"publisher","first-page":"777","DOI":"10.1016\/j.clp.2008.07.014","volume":"35","author":"HJ McCrea","year":"2008","unstructured":"McCrea, H. J. & Ment, L. R. The diagnosis, management, and postnatal prevention of intraventricular hemorrhage in the preterm neonate. Clin. Perinatol. 35, 777\u2013792 (2008).","journal-title":"Clin. Perinatol."},{"key":"89905_CR7","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1891\/0730-0832.24.3.55","volume":"24","author":"R Owens","year":"2005","unstructured":"Owens, R. Intraventricular hemorrhage in the premature neonate. Neonatal Netw. 24, 55\u201371 (2005).","journal-title":"Neonatal Netw."},{"key":"89905_CR8","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/S0140-6736(08)60074-4","volume":"371","author":"RL Goldenberg","year":"2008","unstructured":"Goldenberg, R. L., Culhane, J. F., Iams, J. D. & Romero, R. Epidemiology and causes of preterm birth. Lancet 371, 75\u201384 (2008).","journal-title":"Lancet"},{"key":"89905_CR9","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.siny.2016.01.005","volume":"21","author":"B Koullali","year":"2016","unstructured":"Koullali, B., Oudijk, M., Nijman, T., Mol, B. & Pajkrt, E. Risk assessment and management to prevent preterm birth. Semin. Fetal Neonatal Med. 21, 80\u201388 (2016).","journal-title":"Semin. Fetal Neonatal Med."},{"key":"89905_CR10","doi-asserted-by":"crossref","unstructured":"Shivkumar, P.\u00a0V., Priyadarshani, P. & Choksi, N. Preterm labor. Labour Room Emergencies 33\u201338 (2020).","DOI":"10.1007\/978-981-10-4953-8_4"},{"key":"89905_CR11","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2017-018745","volume":"8","author":"M Delnord","year":"2018","unstructured":"Delnord, M., Blondel, B., Prunet, C. & Zeitlin, J. Are risk factors for preterm and early-term live singleton birth the same? a population-based study in france. BMJ Open 8, e018745 (2018).","journal-title":"BMJ Open"},{"key":"89905_CR12","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1093\/aje\/kwv032","volume":"182","author":"KL Grantz","year":"2015","unstructured":"Grantz, K. L. et al. Differences in risk factors for recurrent versus incident preterm delivery. Am. J. Epidemiol. 182, 157\u2013167 (2015).","journal-title":"Am. J. Epidemiol."},{"key":"89905_CR13","doi-asserted-by":"publisher","first-page":"2279","DOI":"10.3390\/jcm10112279","volume":"10","author":"D Kluwgant","year":"2021","unstructured":"Kluwgant, D., Wainstock, T., Sheiner, E. & Pariente, G. Preterm delivery; who is at risk?. J. Clin. Med. 10, 2279 (2021).","journal-title":"J. Clin. Med."},{"key":"89905_CR14","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/S0029-7844(97)00215-9","volume":"90","author":"TF Porter","year":"1997","unstructured":"Porter, T. F., Fraser, A. M., Hunter, C. Y., Ward, R. H. & Varner, M. W. The risk of preterm birth across generations. Obstetr. Gynecol. 90, 63\u201367 (1997).","journal-title":"Obstetr. Gynecol."},{"key":"89905_CR15","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1093\/ije\/27.2.248","volume":"27","author":"A Winkvist","year":"1998","unstructured":"Winkvist, A., Mogren, I. & H\u00f6gberg, U. Familial patterns in birth characteristics: Impact on individual and population risks. Int. J. Epidemiol. 27, 248\u2013254 (1998).","journal-title":"Int. J. Epidemiol."},{"key":"89905_CR16","doi-asserted-by":"publisher","first-page":"1500","DOI":"10.1056\/NEJM200005183422007","volume":"342","author":"RL Goldenberg","year":"2000","unstructured":"Goldenberg, R. L., Hauth, J. C. & Andrews, W. W. Intrauterine infection and preterm delivery. N. Engl. J. Med. 342, 1500\u20131507 (2000).","journal-title":"N. Engl. J. Med."},{"key":"89905_CR17","doi-asserted-by":"publisher","first-page":"46","DOI":"10.14445\/22315381\/IJETT-V70I5P207","volume":"70","author":"R Surendiran","year":"2022","unstructured":"Surendiran, R., Aarthi, R., Thangamani, M., Sugavanam, S. & Sarumathy, R. A systematic review using machine learning algorithms for predicting preterm birth. Int. J. Eng. Trends Technol. 70, 46\u201359 (2022).","journal-title":"Int. J. Eng. Trends Technol."},{"key":"89905_CR18","doi-asserted-by":"publisher","first-page":"586","DOI":"10.3390\/electronics10050586","volume":"10","author":"T W\u0142odarczyk","year":"2021","unstructured":"W\u0142odarczyk, T. et al. Machine learning methods for preterm birth prediction: a review. Electronics 10, 586 (2021).","journal-title":"Electronics"},{"key":"89905_CR19","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1186\/s12916-022-02522-x","volume":"20","author":"A Abraham","year":"2022","unstructured":"Abraham, A. et al. Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth. BMC Med. 20, 333 (2022).","journal-title":"BMC Med."},{"key":"89905_CR20","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1111\/aogs.14475","volume":"102","author":"Q Yang","year":"2023","unstructured":"Yang, Q. et al. Reporting and risk of bias of prediction models based on machine learning methods in preterm birth: a systematic review. Acta Obstet. Gynecol. Scand. 102, 7\u201314 (2023).","journal-title":"Acta Obstet. Gynecol. Scand."},{"key":"89905_CR21","first-page":"452","volume":"12","author":"A Sari","year":"2024","unstructured":"Sari, A., Lakulu, M. M. & Panessai, I. Y. Predicting premature birth during pregnancy using machine learning: A systematic review. Int. J. Intell. Syst. Appl. Eng. 12, 452\u2013463 (2024).","journal-title":"Int. J. Intell. Syst. Appl. Eng."},{"key":"89905_CR22","doi-asserted-by":"crossref","unstructured":"Rocha, T. A. H. et al. Data-driven risk stratification for preterm birth in brazil: a population-based study to develop of a machine learning risk assessment approach. Lancet Region. Health Am.3 (2021).","DOI":"10.1016\/j.lana.2021.100053"},{"key":"89905_CR23","doi-asserted-by":"publisher","first-page":"1291196","DOI":"10.3389\/fdata.2024.1291196","volume":"7","author":"Q-Y Yu","year":"2024","unstructured":"Yu, Q.-Y., Lin, Y., Zhou, Y.-R., Yang, X.-J. & Hemelaar, J. Predicting risk of preterm birth in singleton pregnancies using machine learning algorithms. Front. Big Data 7, 1291196 (2024).","journal-title":"Front. Big Data"},{"key":"89905_CR24","doi-asserted-by":"publisher","first-page":"779","DOI":"10.1186\/s12884-023-06058-7","volume":"23","author":"Y Zhang","year":"2023","unstructured":"Zhang, Y. et al. Establishment of a model for predicting preterm birth based on the machine learning algorithm. BMC Pregnancy Childbirth 23, 779 (2023).","journal-title":"BMC Pregnancy Childbirth"},{"key":"89905_CR25","doi-asserted-by":"publisher","first-page":"1244","DOI":"10.1038\/s41372-021-00992-0","volume":"41","author":"CC Cibulskis","year":"2021","unstructured":"Cibulskis, C. C., Maheshwari, A., Rao, R. & Mathur, A. M. Anemia of prematurity: how low is too low?. J. Perinatol. 41, 1244\u20131257 (2021).","journal-title":"J. Perinatol."},{"key":"89905_CR26","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.spen.2009.09.005","volume":"16","author":"JJ Volpe","year":"2009","unstructured":"Volpe, J. J. The encephalopathy of prematurity-brain injury and impaired brain development inextricably intertwined. Semin. Pediatr. Neurol. 16, 167\u2013178 (2009).","journal-title":"Semin. Pediatr. Neurol."},{"key":"89905_CR27","doi-asserted-by":"publisher","first-page":"31","DOI":"10.17849\/insm-47-01-31-39.1","volume":"47","author":"SJ Rigatti","year":"2017","unstructured":"Rigatti, S. J. Random forest. J. Insurance Med. 47, 31\u201339 (2017).","journal-title":"J. Insurance Med."},{"key":"89905_CR28","doi-asserted-by":"publisher","first-page":"235","DOI":"10.3390\/info15040235","volume":"15","author":"R Guido","year":"2024","unstructured":"Guido, R., Ferrisi, S., Lofaro, D. & Conforti, D. An overview on the advancements of support vector machine models in healthcare applications: A review. Information 15, 235 (2024).","journal-title":"Information"},{"key":"89905_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12884-020-02940-w","volume":"20","author":"B Koullali","year":"2020","unstructured":"Koullali, B. et al. The association between parity and spontaneous preterm birth: a population based study. BMC Pregnancy Childbirth 20, 1\u20138 (2020).","journal-title":"BMC Pregnancy Childbirth"},{"key":"89905_CR30","doi-asserted-by":"publisher","first-page":"1763","DOI":"10.3390\/healthcare11121763","volume":"11","author":"M Szyszka","year":"2023","unstructured":"Szyszka, M. et al. Association between parity and preterm birth-retrospective analysis from a single center in Poland. Healthcare 11, 1763 (2023).","journal-title":"Healthcare"},{"key":"89905_CR31","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.annepidem.2023.09.004","volume":"87","author":"K Ytterberg","year":"2023","unstructured":"Ytterberg, K. et al. Exploring the association of parity and its interaction with history of preterm delivery on gestational duration. Ann. Epidemiol. 87, 60\u201368 (2023).","journal-title":"Ann. Epidemiol."},{"key":"89905_CR32","doi-asserted-by":"publisher","first-page":"1108","DOI":"10.1093\/aje\/kwi323","volume":"162","author":"W Pitiphat","year":"2005","unstructured":"Pitiphat, W. et al. Plasma c-reactive protein in early pregnancy and preterm delivery. Am. J. Epidemiol. 162, 1108\u20131113 (2005).","journal-title":"Am. J. Epidemiol."},{"key":"89905_CR33","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1055\/s-0030-1249366","volume":"27","author":"Y Sorokin","year":"2010","unstructured":"Sorokin, Y. et al. Maternal serum interleukin-6, c-reactive protein, and matrix metalloproteinase-9 concentrations as risk factors for preterm birth< 32 weeks and adverse neonatal outcomes. Am. J. Perinatol. 27, 631\u2013640 (2010).","journal-title":"Am. J. Perinatol."},{"key":"89905_CR34","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1111\/aji.12265","volume":"72","author":"KK Ferguson","year":"2014","unstructured":"Ferguson, K. K., McElrath, T. F., Chen, Y.-H., Mukherjee, B. & Meeker, J. D. Longitudinal profiling of inflammatory cytokines and c-reactive protein during uncomplicated and preterm pregnancy. Am. J. Reprod. Immunol. 72, 326\u2013336 (2014).","journal-title":"Am. J. Reprod. Immunol."},{"key":"89905_CR35","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.clnesp.2023.05.003","volume":"56","author":"R Khezri","year":"2023","unstructured":"Khezri, R., Salarilak, S. & Jahanian, S. The association between maternal anemia during pregnancy and preterm birth. Clin. Nutr. ESPEN 56, 13\u201317 (2023).","journal-title":"Clin. Nutr. ESPEN"},{"key":"89905_CR36","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1097\/NMC.0000000000000787","volume":"47","author":"AY Stanley","year":"2022","unstructured":"Stanley, A. Y., Wallace, J. B., Hernandez, A. M. & Spell, J. L. Anemia in pregnancy: Screening and clinical management strategies. MCN Am. J. Matern.\/Child Nurs. 47, 25\u201332 (2022).","journal-title":"MCN Am. J. Matern.\/Child Nurs."},{"key":"89905_CR37","doi-asserted-by":"publisher","first-page":"2679","DOI":"10.1080\/14767058.2018.1555811","volume":"33","author":"S Rahmati","year":"2020","unstructured":"Rahmati, S., Azami, M., Badfar, G., Parizad, N. & Sayehmiri, K. The relationship between maternal anemia during pregnancy with preterm birth: a systematic review and meta-analysis. J. Matern.-Fetal Neonatal Med. 33, 2679\u20132689 (2020).","journal-title":"J. Matern.-Fetal Neonatal Med."},{"key":"89905_CR38","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1080\/01443615.2017.1399990","volume":"38","author":"C Gezer","year":"2018","unstructured":"Gezer, C. et al. Identification of preterm birth in women with threatened preterm labour between 34 and 37 weeks of gestation. J. Obstet. Gynaecol. 38, 652\u2013657 (2018).","journal-title":"J. Obstet. Gynaecol."},{"key":"89905_CR39","first-page":"5489","volume":"26","author":"Y Zhang","year":"2022","unstructured":"Zhang, Y., Zhen, M., Zeng, Y., Lao, L. & Ai, W. Complete blood count during the first trimester predicting spontaneous preterm birth. Eur. Rev. Med. Pharmacol. Sci. 26, 5489\u20135495 (2022).","journal-title":"Eur. Rev. Med. Pharmacol. Sci."},{"key":"89905_CR40","doi-asserted-by":"publisher","first-page":"342","DOI":"10.3390\/children10020342","volume":"10","author":"T Okui","year":"2023","unstructured":"Okui, T. Analysis of an association between preterm birth and parental educational level in Japan using national data. Children 10, 342 (2023).","journal-title":"Children"},{"key":"89905_CR41","doi-asserted-by":"publisher","first-page":"e0283901","DOI":"10.1371\/journal.pone.0283901","volume":"18","author":"L Gran\u00e9s","year":"2023","unstructured":"Gran\u00e9s, L., Tor\u00e0-Rocamora, I., Palacio, M., De la Torre, L. & Llupi\u00e0, A. Maternal educational level and preterm birth: Exploring inequalities in a hospital-based cohort study. PLoS ONE 18, e0283901 (2023).","journal-title":"PLoS ONE"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-89905-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-89905-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-89905-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,16]],"date-time":"2025-02-16T11:42:10Z","timestamp":1739706130000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-89905-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,16]]},"references-count":41,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["89905"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-89905-1","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,16]]},"assertion":[{"value":"21 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 February 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 February 2025","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":"Competing interests"}},{"value":"The project was approved by the Ethics Committee of the Nicolaus Copernicus University in Toru\u0144 Collegium Medicum in Bydgoszcz (decision no. KB 443\/2019.) Informed consent was obtained from all subjects involved in the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"5683"}}