An effective Leveraging Ensembling Methods for High-Enactment Chronic Disease Prediction Systems

Authors

  • Manuel R. Tanpoco Assistant Professor, Department of Decision Sciences and Innovation, De La Salle University
  • Preeti Patil Associate Professor, Department of Information Technology, D.Y.Patil College of Engineering, Akurdi, Pune, India
  • Uttara Patnaik District Program Manager, National Ayush Mission, Orissa, India
  • Aniruddha Bodhankar Department of Management, Assistant Professor, Dr.Ambedkar Institute of Management Studies & Research,Nagpur
  • Senthil Kumar A. Professor, Artificial intelligence, University and city with country name: Sri Vishnu Engineering College for Women
  • T. R. Vijaya Lakshmi Associate Professor, ECE, Mahatma Gandhi Institute of Technology

Keywords:

SVM, LR, CVD, Chronic diseases

Abstract

A large portion of the Indian population cannot simply access healthcare facilities. Private hospitals located in and around towns and cities are the primary providers of medical care. Because of this, patients in remote towns and villages must travel great distances to receive basic and specialized medical care. It has been noted that consumers only seek medical attention from a doctor or other medical professional when all other home cures have failed to relieve their symptoms. This is likely due to a lack of understanding as well as other behavioural variables. A novel approach to ensembling was created by the researchers. Results from experiments validate the effectiveness of the proposed strategy in boosting the classification accuracy. The disease prediction system developed in this study showed promising results and has use in the early detection of chronic diseases. The increasing death toll from chronic illness can be combated with the help of these prototypes. The introduction of these chronic disease prediction systems in primary care settings would be a major improvement in healthcare quality. The scope of this study will be broadened to incorporate the creation of prediction models for other diseases.

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Published

11.07.2023

How to Cite

Tanpoco , M. R., Patil, P. ., Patnaik, U. ., Bodhankar, A. ., A., S. K. ., & Lakshmi , T. R. V. . (2023). An effective Leveraging Ensembling Methods for High-Enactment Chronic Disease Prediction Systems. International Journal of Intelligent Systems and Applications in Engineering, 11(8s), 568–575. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3088

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