Ensemble learning-based feature engineering to analyze maternal health during pregnancy and health risk prediction

Maternal health is an important aspect of women’s health during pregnancy, childbirth, and the postpartum period. Specifically, during pregnancy, different health factors like age, blood disorders, heart rate, etc. can lead to pregnancy complications. Detecting such health factors can alleviate the...

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Veröffentlicht in:	PloS one 2022-11, Vol.17 (11), p.e0276525-e0276525
Hauptverfasser:	Raza, Ali, Siddiqui, Hafeez Ur Rehman, Munir, Kashif, Almutairi, Mubarak, Rustam, Furqan, Ashraf, Imran
Format:	Artikel
Sprache:	eng
Schlagworte:	Analysis Artificial neural networks Blood pressure Childbirth & labor Complications Computer and Information Sciences Computer architecture Data analysis Decision trees Ensemble learning Evaluation Fatalities Health aspects Health risk assessment Health risks Heart rate Hematological diseases Learning strategies Long short-term memory Machine learning Maternal health services Medicine and Health Sciences Methods Neural networks Pregnancy Pregnancy complications Pregnant women Risk reduction Support vector machines Womens health
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