Chronic Kidney Disease (CKD) Detection Analysis Using Machine Learning (original) (raw)

Abstract

A chronic kidney disease (CKD) is one of the twenty most common causes of death worldwide, affecting around 10% of adults. Kidney disease damages the kidneys and disrupts their normal function. As CKD prevalence increases, it is increasingly important to have effective predictions for the early diagnosis of the disease. There are many risks associated with chronic kidney disease, including heart disease, breast cancer, urinary tract inflammation (UTI), and infertility. For medical experts, diagnosing CKD at a very early stage is very difficult. It is possible to detect CKD early by using computer-aided diagnostic methods. As a part of computer-aided diagnostics and medical applications, machine learning is essential for detecting diseases and its stages. This paper provides an investigation of various algorithms and methods used in detection of Chronic Kidney Disease and its stages. This survey also identifies research gaps and suggests future research directions.

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Authors and Affiliations

  1. SRM Institute of Science and Technology, Chengalpattu, Tamilnadu, India
    E. Chandralekha & T. R. Saravanan
  2. Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, Avadi, Tamilnadu, India
    N. Vijayaraj

Authors

  1. E. Chandralekha
  2. T. R. Saravanan
  3. N. Vijayaraj

Corresponding author

Correspondence toT. R. Saravanan .

Editor information

Editors and Affiliations

  1. SRM Institute of Science and Technology, Chennai, Tamil Nadu, India
    Annie Uthra R.
  2. Department of Computer Technology, Anna University, Chennai, Tamil Nadu, India
    Kottilingam Kottursamy
  3. Department of Computer Technology, Anna University, Chennai, Tamil Nadu, India
    Gunasekaran Raja
  4. Manchester Metropolitan University, Manchester, UK
    Ali Kashif Bashir
  5. Department of Computer Engineering, Süleyman Demirel University, Isparta, Türkiye
    Utku Kose
  6. SRM Institute of Science and Technology, Chennai, Tamil Nadu, India
    Revathi Appavoo
  7. SRM Institute of Science and Technology, Chennai, Tamil Nadu, India
    Vimaladevi Madhivanan

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Chandralekha, E., Saravanan, T.R., Vijayaraj, N. (2024). Chronic Kidney Disease (CKD) Detection Analysis Using Machine Learning. In: R., A.U., et al. Deep Sciences for Computing and Communications. IconDeepCom 2023. Communications in Computer and Information Science, vol 2176. Springer, Cham. https://doi.org/10.1007/978-3-031-68905-5\_16

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