Machine Learning-Based Prediction Algorithms for the Mitigation of Maternal and Fetal Mortality in the Nigerian Tertiary Hospitals
Résumé
Abstract
Maternal and fetal mortality rates in Nigeria remain among the highest globally, posing a significant public health
challenge. Despite efforts to improve healthcare infrastructure and access, these mortality rates persist at
alarming levels. Recent advancements in Machine Learning (ML) have opened new avenues for addressing this
issue by predicting and mitigating the risks associated with maternal and fetal health complications. This article
reviews the current landscape of ML-based prediction algorithms in Nigerian tertiary hospitals, their potential
impact on healthcare outcomes, future prospects, as well as the challenges and opportunities for its
implementation.
Domaines
Sciences de l'ingénieur [physics]
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