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Machine Learning-Based Prediction Algorithms for the Mitigation of Maternal and Fetal Mortality in the Nigerian Tertiary Hospitals

Domain:

healthcare

Record type:

paper
Creator:
ChaChaSom
Editor:
Nna
Publisher:
CCSD
Host:avatar
International audience AbstractMaternal 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 itsimplementation.

Tags

Nigerian tertiary hospitals -----------fetal mortalitymaternal mortalityhealthcareprediction algorithmsmachine learningmachine learning prediction algorithms healthcare maternal mortality fetal mortality Nigerian tertiary hospitals -----------[SPI]Engineering Sciences [physics]

Licenses

info:eu-repo/semantics/OpenAccess

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