{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T04:10:26Z","timestamp":1774671026703,"version":"3.50.1"},"reference-count":75,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,7]],"date-time":"2022-07-07T00:00:00Z","timestamp":1657152000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund","award":["MCIU\/AEI\/FEDER"],"award-info":[{"award-number":["MCIU\/AEI\/FEDER"]}]},{"name":"Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund","award":["UE RTI2018-094449-A-I00-AR"],"award-info":[{"award-number":["UE RTI2018-094449-A-I00-AR"]}]},{"name":"Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund","award":["AICO\/2019\/220"],"award-info":[{"award-number":["AICO\/2019\/220"]}]},{"DOI":"10.13039\/501100003359","name":"Generalitat Valenciana","doi-asserted-by":"publisher","award":["MCIU\/AEI\/FEDER"],"award-info":[{"award-number":["MCIU\/AEI\/FEDER"]}],"id":[{"id":"10.13039\/501100003359","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003359","name":"Generalitat Valenciana","doi-asserted-by":"publisher","award":["UE RTI2018-094449-A-I00-AR"],"award-info":[{"award-number":["UE RTI2018-094449-A-I00-AR"]}],"id":[{"id":"10.13039\/501100003359","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003359","name":"Generalitat Valenciana","doi-asserted-by":"publisher","award":["AICO\/2019\/220"],"award-info":[{"award-number":["AICO\/2019\/220"]}],"id":[{"id":"10.13039\/501100003359","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to its high sensitivity, electrohysterography (EHG) has emerged as an alternative technique for predicting preterm labor. The main obstacle in designing preterm labor prediction models is the inherent preterm\/term imbalance ratio, which can give rise to relatively low performance. Numerous studies obtained promising preterm labor prediction results using the synthetic minority oversampling technique. However, these studies generally overestimate mathematical models\u2019 real generalization capacity by generating synthetic data before splitting the dataset, leaking information between the training and testing partitions and thus reducing the complexity of the classification task. In this work, we analyzed the effect of combining feature selection and resampling methods to overcome the class imbalance problem for predicting preterm labor by EHG. We assessed undersampling, oversampling, and hybrid methods applied to the training and validation dataset during feature selection by genetic algorithm, and analyzed the resampling effect on training data after obtaining the optimized feature subset. The best strategy consisted of undersampling the majority class of the validation dataset to 1:1 during feature selection, without subsequent resampling of the training data, achieving an AUC of 94.5 \u00b1 4.6%, average precision of 84.5 \u00b1 11.7%, maximum F1-score of 79.6 \u00b1 13.8%, and recall of 89.8 \u00b1 12.1%. Our results outperformed the techniques currently used in clinical practice, suggesting the EHG could be used to predict preterm labor in clinics.<\/jats:p>","DOI":"10.3390\/s22145098","type":"journal-article","created":{"date-parts":[[2022,7,7]],"date-time":"2022-07-07T07:51:56Z","timestamp":1657180316000},"page":"5098","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0050-9360","authenticated-orcid":false,"given":"F\u00e9lix","family":"Nieto-del-Amor","sequence":"first","affiliation":[{"name":"Centro de Investigaci\u00f3n e Innovaci\u00f3n en Bioingenier\u00eda, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9362-5055","authenticated-orcid":false,"given":"Gema","family":"Prats-Boluda","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n e Innovaci\u00f3n en Bioingenier\u00eda, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1410-2721","authenticated-orcid":false,"given":"Javier","family":"Garcia-Casado","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n e Innovaci\u00f3n en Bioingenier\u00eda, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4605-6048","authenticated-orcid":false,"given":"Alba","family":"Diaz-Martinez","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n e Innovaci\u00f3n en Bioingenier\u00eda, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vicente Jose","family":"Diago-Almela","sequence":"additional","affiliation":[{"name":"Servicio de Obstetricia, H.U.P. La Fe, 46026 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rogelio","family":"Monfort-Ortiz","sequence":"additional","affiliation":[{"name":"Servicio de Obstetricia, H.U.P. La Fe, 46026 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5715-5930","authenticated-orcid":false,"given":"Dongmei","family":"Hao","sequence":"additional","affiliation":[{"name":"Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2929-181X","authenticated-orcid":false,"given":"Yiyao","family":"Ye-Lin","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n e Innovaci\u00f3n en Bioingenier\u00eda, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"WHO (1977). 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