Machine Learning-Based Prediction Algorithms for the Mitigation of Maternal and Fetal Mortality in the Nigerian Tertiary Hospitals - Archive ouverte HAL
Article Dans Une Revue International Journal of Engineering Inventions Année : 2024

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.
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Dates et versions

hal-04669409 , version 1 (20-08-2024)

Identifiants

  • HAL Id : hal-04669409 , version 1

Citer

Nwamekwe Charles Onyeka, Okpala Charles Chikwendu, Okpala Somkenechi Chinwe. Machine Learning-Based Prediction Algorithms for the Mitigation of Maternal and Fetal Mortality in the Nigerian Tertiary Hospitals. International Journal of Engineering Inventions, 2024, 13 (7), pp.132 - 138. ⟨hal-04669409⟩
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