Abstract
Newborns are fragile and have a high risk of dying within the first 28 days of their life, therefore they require quality care from conception. This research aims at implementing a mobile pediatric diagnostic system for the rural settlers in Nigeria, reducing childhood mortality and providing an alternative pediatric professional. 581 records classified with naïve Bayes and decision-stump-tree classifier gave a higher accuracy level for naïve Bayes. A decision-support system is developed to aid health workers in rural areas in providing quality health service for children below six, which will provide low-cost medical service and contribute to reducing childhood mortality.
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We acknowledge the support and sponsorship provided by Covenant University through the Centre for Research, Innovation and Discovery (CUCRID).
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Iheme, P., Omoregbe, N., Misra, S., Ayeni, F., Adeloye, D. (2018). A Decision Support System for Pediatric Diagnosis. In: M. F. Kebe, C., Gueye, A., Ndiaye, A. (eds) Innovation and Interdisciplinary Solutions for Underserved Areas. CNRIA InterSol 2017 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 204. Springer, Cham. https://doi.org/10.1007/978-3-319-72965-7_17
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DOI: https://doi.org/10.1007/978-3-319-72965-7_17
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