Prediction of clinical events in hemodialysis patients using an artificial neural network

Firdani Rianda Putra, Aldilas Achmad Nursetyo, Saurabh Singh Thakur, Ram Babu Roy, Shabbir Syed-Abdul, Shwetambara Malwade, Yu Chuan Lia

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

1 Citation (Scopus)

Abstract

Advanced chronic kidney disease (CKD) requires routine renal replacement therapy (RRT) that involves hemodialysis (HD) which may cause increased risk of muscle spasms, cardiovascular events, and death. We used Artificial Neural Network (ANN) method to predict clinical events during the HD sessions. The vital signs, captured using a non-contact bed-sensor, and demographic information from the electronic medical records for 109 patients enrolled in the study was used. Weka Workbench software was used to train and validate the ANN model. The prediction model was built using a Multilayer perceptron (MLP) algorithm as part of the ANN with 10-fold cross-validation. The model showed mean precision and recall of 93.45% and AUC of 96.7%. Age was the most important variable for static feature and heart rate for dynamic feature. This model can be used to predict the risk of clinical events among HD patients and can support decision-making for healthcare professionals.

Original languageEnglish
Title of host publicationMEDINFO 2019
Subtitle of host publicationHealth and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics
EditorsBrigitte Seroussi, Lucila Ohno-Machado, Lucila Ohno-Machado, Brigitte Seroussi
PublisherIOS Press
Pages1570-1571
Number of pages2
ISBN (Electronic)9781643680026
DOIs
Publication statusPublished - Aug 21 2019
Event17th World Congress on Medical and Health Informatics, MEDINFO 2019 - Lyon, France
Duration: Aug 25 2019Aug 30 2019

Publication series

NameStudies in Health Technology and Informatics
Volume264
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference17th World Congress on Medical and Health Informatics, MEDINFO 2019
CountryFrance
CityLyon
Period8/25/198/30/19

Keywords

  • Electronic health records
  • Neural networks
  • Renal dialysis

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Fingerprint Dive into the research topics of 'Prediction of clinical events in hemodialysis patients using an artificial neural network'. Together they form a unique fingerprint.

  • Cite this

    Putra, F. R., Nursetyo, A. A., Thakur, S. S., Roy, R. B., Syed-Abdul, S., Malwade, S., & Lia, Y. C. (2019). Prediction of clinical events in hemodialysis patients using an artificial neural network. In B. Seroussi, L. Ohno-Machado, L. Ohno-Machado, & B. Seroussi (Eds.), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics (pp. 1570-1571). (Studies in Health Technology and Informatics; Vol. 264). IOS Press. https://doi.org/10.3233/SHTI190539