Usage of Information Computing Technology, Data Mining, and Machine Learning to Reduce Child Mortality and Morbidity: Case Study Afghanistan

Ihsanullah Nazari

Usage of Information Computing Technology, Data Mining, and Machine Learning to Reduce Child Mortality and Morbidity: Case Study Afghanistan

Ihsanullah Nazari

Volume 1 Issue 1 | Dec 2024

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Abstract

Child mortality and morbidity are critical global health challenges, with the highest rates found in developing countries. In Afghanistan, the under-five mortality rate is 57 per 1000 live births, a significant figure in 2022, which is a staggering number. Challenges include insufficient doctors, lack of awareness among people, inadequate health facilities, poor health management information systems, cultural barriers, infrastructure and transportation issues, remote areas without health facilities, and climate challenges like prolonged snowfall in some provinces. Recently, Afghanistan has seen significant advancements in information technology. This paper proposes using machine learning and data mining techniques to predict the danger level of children’s health problems, aiming to reduce child mortality and morbidity.
Keywords: Mortality, Morbidity, Bayesian Logistic Regression, K-Nearest Neighbor