Machine learning for high risk pregnancies pre-term birth prediction: A retrospective

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dc.contributor.authorRamla, M
dc.contributor.authorSangeetha, S
dc.contributor.authorNickolas, S
dc.date.accessioned2026-11-11T05:22:28Z
dc.date.available2026-11-11T05:22:28Z
dc.date.issued2018-04-20
dc.description.abstractAny birth before 28 weeks of gestation is termed as Pre-Term. This has substantial impact in the emotional reactions of mothers. The post-traumatic stress notably in the mother could be of chronic psychological risk. Moreover, it is to be addressed in the global scenario for sustainable development. Predicting stillbirths is still a distant reality. A plethora of works have been carried out and this paper present the summaries and analysis of current research. The primary focus of the paper is to throw light on the challenging issue of Preterm Birth Prediction. Myriad of machine learning techniques are used by various researchers each with its own estimation accuracy and type of ML model.
dc.identifier.issn2227524X
dc.identifier.urihttps://doi.org/10.14419/ijet.v7i2.22.11799
dc.identifier.urihttp://nitt.ndl.gov.in/handle/123456789/428
dc.language.isoen
dc.publisherScience Publishing Corporation Inc
dc.relation.ispartofseriesInternational Journal of Engineering and Technology(UAE); Vol. 7/ No. 2
dc.titleMachine learning for high risk pregnancies pre-term birth prediction: A retrospective
dc.typeArticle
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