Article citationsMore>>

Rizzi, S., Bertino, E., Catania, B., Golfarelli, M., Halkidi, M., Terrovitis, M., Vassiliadis, P., Vazirgiannis, M. and Vrachnos, E. (2003) Towards a Logical Model for Patterns in ER. Springer, Chicago, Vol. 2813, 77-90.
https://doi.org/10.1007/978-3-540-39648-2_9

has been cited by the following article:

• TITLE: Data Mining as a Technique for Healthcare Approach

  AUTHORS: E. N. Ekwonwune, C. I. Ubochi, A. E. Duroha

  KEYWORDS: Data Mining, Techniques, Relational Database, Knowledge, Clustering, Classification, Regression, Healthcare

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.15 No.9, September 30, 2022

  ABSTRACT: Data Mining, also known as knowledge discovery in data (KDC), is the process of uncovering patterns and other valuable information from large data sets. According to https://www.geeksforgeeks.org/data-mining/, it can be referred to as knowledge mining from data, knowledge extraction, data/pattern analysis, data archaeology, and data dredging. With advance research in health sector, there is multitude of Data available in healthcare sector. The general problem then becomes how to use the existing information in a more useful targeted way. Data Mining therefore is the best available technique. The objective of this paper is to review and analyse some of the different Data Mining Techniques such as Application, Classification, Clustering, Regression, etc. applied in the Domain of Healthcare.