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LEVERAGING MACHINE LEARNING FOR EARLY DETECTION AND PREDICTION OF CHOLERA OUTBREAKS IN NIGERIA: A DATA-DRIVEN APPROACH

Domaine:

healthcare

Type de record:

paper
Créateur:
OmaEtu
Éditeur:
The
Hôte:avatar
Cholera remains a significant public health challenge in Nigeria, causing numerous fatalities annually. This study aims to develop a machine learning-based predictive model for early detection and prediction of cholera outbreaks in Nigeria. By integrating diverse datasets, including environmental, socio-economic, and health data, the model offers actionable insights to public health officials, enabling timely interventions and resource allocation. The study utilizes various machine learning algorithms to analyze historical data, with Random Forest emerging as the most effective. The model's predictions, validated against actual outbreak data, demonstrate its potential to significantly enhance outbreak preparedness and response strategies.

Visit

doi.orgnampjournals.org.ng

Tags

Cholera PredictionMachine LearningPublic HealthNigeriaInfectious Disease Modeling.

Licenses

Creative Commons Attribution Non Commercial 4.0 Internationalhttps://creativecommons.org/licenses/by-nc/4.0/legalcode

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