{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T07:56:40Z","timestamp":1790409400350,"version":"4.1.0"},"reference-count":59,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,28]],"date-time":"2024-04-28T00:00:00Z","timestamp":1714262400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Technology of China","award":["G2021171024L"],"award-info":[{"award-number":["G2021171024L"]}]},{"name":"Ministry of Science and Technology of China","award":["300203110029"],"award-info":[{"award-number":["300203110029"]}]},{"name":"Ministry of Science and Technology of China","award":["300201000173"],"award-info":[{"award-number":["300201000173"]}]},{"DOI":"10.13039\/100010014","name":"High-Level Talent Project of Chang\u2019an University","doi-asserted-by":"publisher","award":["G2021171024L"],"award-info":[{"award-number":["G2021171024L"]}],"id":[{"id":"10.13039\/100010014","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010014","name":"High-Level Talent Project of Chang\u2019an University","doi-asserted-by":"publisher","award":["300203110029"],"award-info":[{"award-number":["300203110029"]}],"id":[{"id":"10.13039\/100010014","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010014","name":"High-Level Talent Project of Chang\u2019an University","doi-asserted-by":"publisher","award":["300201000173"],"award-info":[{"award-number":["300201000173"]}],"id":[{"id":"10.13039\/100010014","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shaanxi Province","award":["G2021171024L"],"award-info":[{"award-number":["G2021171024L"]}]},{"name":"Shaanxi Province","award":["300203110029"],"award-info":[{"award-number":["300203110029"]}]},{"name":"Shaanxi Province","award":["300201000173"],"award-info":[{"award-number":["300201000173"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Early pregnancy loss (EPL) is a prevalent health concern with significant implications globally for gestational health. This research leverages machine learning to enhance the prediction of EPL and to differentiate between typical pregnancies and those at elevated risk during the initial trimester. We employed different machine learning methodologies, from conventional models to more advanced ones such as deep learning and multilayer perceptron models. Results from both classical and advanced machine learning models were evaluated using confusion matrices, cross-validation techniques, and analysis of feature significance to obtain correct decisions among algorithmic strategies on early pregnancy loss and the vitamin D serum connection in gestational health. The results demonstrated that machine learning is a powerful tool for accurately predicting EPL, with advanced models such as deep learning and multilayer perceptron outperforming classical ones. Linear discriminant analysis and quadratic discriminant analysis algorithms were shown to have 98 % accuracy in predicting pregnancy loss outcomes. Key determinants of EPL were identified, including levels of maternal serum vitamin D. In addition, prior pregnancy outcomes and maternal age are crucial factors in gestational health. This study\u2019s findings highlight the potential of machine learning in enhancing predictions related to EPL that can contribute to improved gestational health outcomes for mothers and infants.<\/jats:p>","DOI":"10.3390\/diagnostics14090920","type":"journal-article","created":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T11:39:42Z","timestamp":1714649982000},"page":"920","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Innovative Machine Learning Strategies for Early Detection and Prevention of Pregnancy Loss: The Vitamin D Connection and Gestational Health"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3503-6942","authenticated-orcid":false,"given":"Md Abu","family":"Sufian","sequence":"first","affiliation":[{"name":"IVR Low-Carbon Research Institute, Chang\u2019an University, Xi\u2019an 710018, China"},{"name":"School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wahiba","family":"Hamzi","sequence":"additional","affiliation":[{"name":"Laboratoire de Biotechnologie, Environnement et Sant\u00e9, Department of Biology, University of Blida, Blida 09000, Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boumediene","family":"Hamzi","sequence":"additional","affiliation":[{"name":"Department of Computing and Mathematical Sciences, California Institute of Technology, Caltech, CA 91125, USA"},{"name":"The Alan Turing Institute, London NW1 2DB, UK"},{"name":"Department of Mathematics, Gulf University for Science and Technology (GUST), Mubarak Al-Abdullah 32093, Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4891-0233","authenticated-orcid":false,"given":"A. S. M. Sharifuzzaman","family":"Sagar","sequence":"additional","affiliation":[{"name":"Department of AI and Robotics, Sejong University, Seoul 05006, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mustafizur","family":"Rahman","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, Tsinghua University, Beijing 100084, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2778-1265","authenticated-orcid":false,"given":"Jayasree","family":"Varadarajan","sequence":"additional","affiliation":[{"name":"Centre for Digital Innovation, Manchester Metropolitan University, Manchester M15 6BH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2209-6448","authenticated-orcid":false,"given":"Mahesh","family":"Hanumanthu","sequence":"additional","affiliation":[{"name":"School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md Abul Kalam","family":"Azad","sequence":"additional","affiliation":[{"name":"Department of Medicine, Rangpur Medical College and Hospital, Rangpur 5400, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1038\/ejcn.2016.83","article-title":"Decreased serum vitamin D levels in early spontaneous pregnancy loss","volume":"70","author":"Hou","year":"2016","journal-title":"Eur. 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