A Review on Divergent Application Architecture of Big Data Mining in Healthcare

Authors

  • Vibha Sahu  PG Scholar, Department of Computer Science and Engineering, TRUBA College, Bhopal, Madhya Pradesh, India
  • Prof. Ritu Chaturvedi  Professor, Department of Computer Science and Engineering, TRUBA College, Bhopal, Madhya Pradesh, India
  • Dr. Kaptan Singh  Professor, Department of Computer Science and Engineering, TRUBA College, Bhopal, Madhya Pradesh, India

Keywords:

Data Mining, Classification, Clustering, Association, Healthcare

Abstract

Data mining one of the most important motivating fields of research is data mining that also is becoming becoming more prominent in the healthcare field. Data mining anticipates a purpose for discovering developments in crucial fitness care organizations that progressively benefit all parties participating in this self-control. This digest references to the utilization of numerous quantitative processing techniques, also including class, clustering, association, etc regression, in the subject area of fitness. These approaches, together along with their benefits and drawbacks, are briefly discussed in this paper. Additionally, this compendium centre’s on the packages, difficulties, and approaching challenges of anthropology treatment in the appropriate putting away. This report also contains a declaration of support for the traditional elite of feasible information processing methods.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-02-28

Issue

Volume 9, Issue 1, January-February-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Vibha Sahu, Prof. Ritu Chaturvedi, Dr. Kaptan Singh, " A Review on Divergent Application Architecture of Big Data Mining in Healthcare " International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 1, pp.38-45, January-February-2023.