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Innovation and Interdisciplinary Solutions for Underserved Areas. First International Conference, InterSol 2017 and Sixth Collogue National sur la Recherche en Informatique et ses Applications, CNRIA 2017, Dakar, Senegal, April 11–12, 2017, Proceedings

Research Article

A Decision Support System for Pediatric Diagnosis

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  • @INPROCEEDINGS{10.1007/978-3-319-72965-7_17,
        author={Precious Iheme and Nicholas Omoregbe and Sanjay Misra and Foluso Ayeni and Davies Adeloye},
        title={A Decision Support System for Pediatric Diagnosis},
        proceedings={Innovation and Interdisciplinary Solutions for Underserved Areas. First International Conference, InterSol 2017 and Sixth Collogue National sur la Recherche en Informatique et ses Applications, CNRIA 2017, Dakar, Senegal, April 11--12, 2017, Proceedings},
        proceedings_a={INTERSOL \& CNRIA},
        year={2018},
        month={2},
        keywords={Child healthcare Mobile technology Na\~{n}ve bayes Pediatric disease},
        doi={10.1007/978-3-319-72965-7_17}
    }
    
  • Precious Iheme
    Nicholas Omoregbe
    Sanjay Misra
    Foluso Ayeni
    Davies Adeloye
    Year: 2018
    A Decision Support System for Pediatric Diagnosis
    INTERSOL & CNRIA
    Springer
    DOI: 10.1007/978-3-319-72965-7_17
Precious Iheme1,*, Nicholas Omoregbe1,*, Sanjay Misra1,*, Foluso Ayeni1,*, Davies Adeloye1,*
  • 1: Covenant University
*Contact email: Precious.Iheme@covenantuniversity.edu.ng, Nicholas.Omoregbe@covenantuniversity.edu.ng, Sanjay.Misra@covenantuniversity.edu.ng, Foluso.Ayeni@covenantuniversity.edu.ng, Davies.Adeloye@covenantuniversity.edu.ng

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.

Keywords
Child healthcare Mobile technology Naïve bayes Pediatric disease
Published
2018-02-01
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-319-72965-7_17
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