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:: Volume 27, Issue 5 (Bimonthly 2023) ::
Feyz Med Sci J 2023, 27(5): 559-565 Back to browse issues page
Prediction of hepatic encephalopathy complication in liver transplant patients using support vector machine algorithm in active middle-aged women
Bakhtyar Tartibian * , Leila Fasihi , Rasoul Eslami , Ahmad Fasihi
Department of Exercise Physiology, Faculty of Physical Education and Sport Sciences, Allameh Tabataba'i University, Tehran, Iran , ba.tartibian@gmail.com
Abstract:   (797 Views)
Background and Aim: In liver transplant patients, the occurrence of postoperative complications increases the length of hospitalization, care of patients and the costs of treatment. The aim of this study was to predict the complications of hepatic encephalopathy in liver transplant patients using the support vector machine (SVM) algorithm in active middle-aged women.
Methods: The statistical population included 652 patients, among them, 165 active middle-aged women with encephalopathy symptoms who underwent liver transplantation during 2011-2022 were included. SVM algorithm was used to predict the complications of hepatic encephalopathy in liver transplant patients and MATLAB software was used for data analysis.
Results: Using 14 features related to laboratory, anthropometry and lifestyle data, the SVM algorithm can predict people with and without hepatic encephalopathy complications with 81.2% accuracy and 74.6% precision.
Conclusion: According to the accuracy of the SVM algorithm on the data, it seems that this system may help physicians predict the risk of hepatic encephalopathy complications after transplantation with high accuracy and the lowest cost. Computer-based decision support systems can reduce poor clinical decisions and also minimize costs associated with unnecessary clinical trials.
Keywords: Liver transplantation, Encephalopathy, Support vector machine algorithm, Middle-aged wome
Full-Text [PDF 506 kb]   (475 Downloads)    
Type of Study: Research | Subject: medicine, paraclinic
Received: 2023/04/18 | Revised: 2023/12/13 | Accepted: 2023/11/18 | Published: 2023/12/10
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Tartibian B, Fasihi L, Eslami R, Fasihi A. Prediction of hepatic encephalopathy complication in liver transplant patients using support vector machine algorithm in active middle-aged women. Feyz Med Sci J 2023; 27 (5) :559-565
URL: http://feyz.kaums.ac.ir/article-1-4861-en.html


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Volume 27, Issue 5 (Bimonthly 2023) Back to browse issues page
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