The analysis of the effects of acute rheumatic fever in childhood on cardiac disease with data mining

Emre I. E., Erol N., Ayhan Y. I., Ozkan Y., Erol C.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, vol.123, pp.68-75, 2019 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Review
  • Volume: 123
  • Publication Date: 2019
  • Doi Number: 10.1016/j.ijmedinf.2018.12.009
  • Journal Name: INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.68-75
  • Keywords: Data mining, Machine learning, Classifying methods, Naive bayes, C5.0, CART, Random forest, Acute rheumatic fever, Acute rheumatic fever in childhood, ARF, KNOWLEDGE
  • Marmara University Affiliated: Yes

Abstract

Background: Acute rheumatic fever (ARF) is an important disease that is frequently seen in Turkey, it is necessary to develop solutions to cure the disease. It is believed that new data analysis methods may be applied to this disease, and this may be useful to discover previously unrecognized patterns. Data mining of existing records and data repositories may improve knowledge on the diagnosis and management of ARF. In this regard, we planned to make a contribution to the development of new solutions by approaching the problem from a different standpoint.