Machine learning algorithms for predictive modeling of dyslipidemia-associated cardiovascular disease risk in pregnancy: a comparison of boosting, random forest, and decision tree regression

Machine learning algorithms for predictive modeling of dyslipidemia-associated cardiovascular disease risk in pregnancy: a comparison of boosting, random forest, and decision tree regression

Abstract Background Cardiovascular diseases (CVD) are major contributors to maternal mortality and morbidity during pregnancy and increased atherogenic index of plasma levels is associated with a higher risk of CVD and obesity. Methods In this study, we utilized three different machine learning algo...

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Bibliographic Details
Main Authors: Idris Zubairu Sadiq, Fatima Sadiq Abubakar, Muhammad Auwal Saliu, Babangida Sanusi katsayal, Aliyu Salihu, Aliyu Muhammad
Format: Article
Language:English
Published: SpringerOpen 2025-01-01
Series:Bulletin of the National Research Centre
Subjects:
Machine learning
Algorithms
Cardiovascular diseases
Pregnancy
Atherogenic index
Online Access:https://doi.org/10.1186/s42269-024-01295-y
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https://doi.org/10.1186/s42269-024-01295-y

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