Predictive model for the incidence of hyperkalemia for congestive heart failure patients on spironolactone

Reham Aldakhil, Mouaz Almallah Almallah, Sherif Sakr

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

Abstract

The importance of Spironolactone in congestive heart failure (CHF) treatment has been well established. The prediction of the hyperkalemia in the patient using Spironolactone is still not clearly defined. The aim of this study is to develop an accurate prediction model of hyperkalemia incidence in CHF patients on Spironolactone using machine learning techniques. A classification and prediction process have been applied on patients' data of the cardiac center of National Guard Health Affairs, King Abdulaziz Medical City (KAMC). The study was conducted on the records of 1533 patients representing the CHF patient's during the period of 2011-2016. Our experiments show that the JRip classifier achieves the best performance for the Precision (0.983), Recall (0.983), F-measure (0.976) and Accuracy (98.27) metrics while the Naiive Bayesian classifier achieves the best performance for the Specificity (0.652) and AUC (0.93) metrics.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages384-385
Number of pages2
ISBN (Electronic)9781538653777
DOIs
StatePublished - Jul 24 2018
Event6th IEEE International Conference on Healthcare Informatics, ICHI 2018 - New York, United States
Duration: Jun 4 2018Jun 7 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018

Other

Other6th IEEE International Conference on Healthcare Informatics, ICHI 2018
CountryUnited States
CityNew York
Period6/4/186/7/18

Keywords

  • Healthcare Analytics
  • Heart Failure
  • Predictive Model

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Health Informatics

Fingerprint Dive into the research topics of 'Predictive model for the incidence of hyperkalemia for congestive heart failure patients on spironolactone'. Together they form a unique fingerprint.

Cite this