Title
A Survey on Diverse Chronic Disease Prediction Models and Implementation Techniques
Author(s)
Dr. Rohit Kumar Miri
Document Abstract
In today’s world, chronic diseases are a crucial reason for death. The chronic disease is gradually taking the patient into control and then take over. Chronic start slowly and continues for a long time. There is a need to predict chronic disease at early stages before it reaches an uncontrolled situation so timely treatments can resist it. Prediction system effectively controls chronic disease at early stages. Our study
aims to cover various prediction models for chronic disease and techniques for the development of prediction models. This review gives a comprehensive overview of the predictions system and implemented techniques for basic chronic disease. We go through predictionmodels are developed for basic chronic diseases like heart disease, cancer, diabetes and kidney disease with a different set of techniques. The survey
paper discusses an overview of different chronic disease prediction models and its implementation techniques. The survey shows that machine learning approach is efficient to design a prediction system for chronic diseases in the welfare of health organizations and ultimate benefit to patients. This paper reviews basic chronic disease prediction models and suggested that to achieve accurate results of chronic disease
prediction system machine learning is promising.
Subject Name
COMPUTER SCIENCE ENGINEERING
Publisher Name
Intelligent System Design, Advances in Intelligent Systems and Computing
Rights :
all rights reserved at author
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