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A Survey on Diverse Chronic Disease Prediction Models and Implementation Techniques

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Intelligent System Design

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1171))

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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 prediction models 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.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Dr. C. V. Raman University Kota, Bilaspur (C.G.), India

    Nitin Chopde & Rohit Miri

Authors
  1. Nitin Chopde
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  2. Rohit Miri
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Corresponding author

Correspondence to Nitin Chopde .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, KIIT Demmed to be University, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  2. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Department of Computer Science and Engineering, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India

    B. Janakiramaiah

  4. College of Information Science and Engineering, Ritsumeikan University, Kyoto, Japan

    Yen-Wei Chen

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Cite this paper

Chopde, N., Miri, R. (2021). A Survey on Diverse Chronic Disease Prediction Models and Implementation Techniques. In: Satapathy, S., Bhateja, V., Janakiramaiah, B., Chen, YW. (eds) Intelligent System Design. Advances in Intelligent Systems and Computing, vol 1171. Springer, Singapore. https://doi.org/10.1007/978-981-15-5400-1_51

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