Prediction of Clinical Events in Hemodialysis Patients Using an Artificial Neural Network.

Clicks: 196
ID: 21192
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #116 of 170 articles by views in Studies in health technology and informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 170 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
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.
Reference Key
putra2019predictionstudies Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Putra, Firdani Rianda;Nursetyo, Aldilas Achmad;Thakur, Saurabh Singh;Roy, Ram Babu;Syed-Abdul, Shabbir;Malwade, Shwetambara;Li, Yu-Chuan Jack;
Journal Studies in health technology and informatics
Year 2019
DOI
10.3233/SHTI190539
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.