Maternal Nutritional Factors Enhance Birthweight Prediction: A Super Learner Ensemble Approach

Information, Journal Year: 2024, Volume and Issue: 15(11), P. 714 - 714

Published: Nov. 6, 2024

Birthweight (BW) is a widely used indicator of neonatal health, with low birthweight (LBW) being linked to higher risks morbidity and mortality. Timely precise prediction LBW crucial for ensuring newborn health well-being. Despite recent machine learning advancements in BW classification based on physiological traits the mother ultrasound outcomes, maternal status essential micronutrients fetal development yet be fully exploited prediction. This study aims evaluate impact nutritional factors, specifically mid-pregnancy plasma concentrations vitamin B12, folate, anemia analyzed data from 729 pregnant women Tarragona, Spain, early each factor’s contribution using partial dependency plot feature importance. Using super learner ensemble method tenfold cross-validation, model achieved accuracy 96.19% an AUC-ROC 0.96, outperforming single-model approaches. Vitamin B12 folate were identified as significant predictors, underscoring their importance reducing risk. The findings highlight critical role factors suggest that monitoring levels during pregnancy could enhance prenatal care mitigate complications associated LBW.

Language: Английский

A neural network integrated mathematical model to analyze the impact of nutritional status on cognitive development of child

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 185, P. 109490 - 109490

Published: Dec. 9, 2024

Language: Английский