Evidence-Based Technological Approach for Disease Prediction Using Classification Technique

  • Vanishri Arun
  • B. V. Arunkumar
  • S. K. Padma
  • V. Shyam
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 14)

Abstract

Due to the growing population and reduced mortality rate, models of treatment delivery are rapidly changing and many decisions behind these changes are being driven by data. It is now important to understand as much about a patient as possible, in order to pick up warning signs of serious illness at an early stage. In this study, Naïve Bayes approach which is a data mining classification technique is used to model the prediction of Non-Communicable Diseases (NCD) and to give systematic treatment. The project brings about technology-based non-pharmacological and lifestyle modification measures blended together for the NCD control among rural subjects. The benefits of an automated disease prediction system are decreased healthcare costs via early prediction of disease, reduced time consumption and accurate. This provides evidence-based technological approach and can serve as a model for the upcoming national programs for the policy makers in management of NCDs.

Keywords

Data mining Naïve Bayes Non-communicable diseases 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Vanishri Arun
    • 1
  • B. V. Arunkumar
    • 2
  • S. K. Padma
    • 1
  • V. Shyam
    • 3
  1. 1.Department of Information Science and EngineeringSri Jayachamarajendra College of EngineeringMysoreIndia
  2. 2.Apollo BGS HospitalMysoreIndia
  3. 3.Forus Health Private Ltd.BengaluruIndia

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