Heart disease diagnosis system with k-nearest neighbors method using real clinical medical records

I. Ketut Agung Enriko, Muhammad Suryanegara, Dadang Gunawan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Heart disease is a serious disease that can lead to the death of a patient. Many types of research have been performed related to heart disease, including computer science-based research. Heart disease diagnosis studies, which aim to predict the type of heart disease from which a patient suffers, are popular and refer to some clinical parameters taken from the patient in the hospital. These data are then computed using data mining or machine learning techniques. Some algorithms can be utilized for this purpose, for example, Naïve Bayes, Support Vector Machine, and k-Nearest Neighbor algorithms. This research intends to diagnose heart disease using a sample of patient data. The data were collected from Harapan Kita Hospital, the biggest cardiovascular hospital in Indonesia. The patient clinical parameters selected are taken from complete data available in the hospital's medical records. The k-Nearest Neighbor method gave good results for heart disease diagnosis, and these results can be further used for another purpose, such as telemedicine or a machine-to-machine (M2M) based healthcare system.

Original languageEnglish
Title of host publicationProceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018
PublisherAssociation for Computing Machinery
Pages127-131
Number of pages5
ISBN (Print)9781450364720
DOIs
Publication statusPublished - 25 Jun 2018
Event4th International Conference on Frontiers of Educational Technologies, ICFET 2018, Jointly with its Workshop the 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018 - Moscow, Russian Federation
Duration: 25 Jun 201827 Jun 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th International Conference on Frontiers of Educational Technologies, ICFET 2018, Jointly with its Workshop the 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018
CountryRussian Federation
CityMoscow
Period25/06/1827/06/18

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Keywords

  • Data mining
  • K-Nearest Neighbor
  • Machine learning
  • Machine learning algorithms

Cite this

Enriko, I. K. A., Suryanegara, M., & Gunawan, D. (2018). Heart disease diagnosis system with k-nearest neighbors method using real clinical medical records. In Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018 (pp. 127-131). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3233347.3233386