Zhenisgul Rakhmetullina
D. Serikbayev East Kazakhstan Technical University

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Research and implementation of the medical text analysis algorithm for predicting mortality Zhenisgul Rakhmetullina; Saule Belginova; Alibekkyzy Karlygash; Aigerim Ismukhamedova; Shynar Tezekpaeva
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1965-1977

Abstract

Mortality prediction has a role to play in the development of a descriptive measure of the quality of care that provides a fair and equitable means of comparing and evaluating hospitals. This article describes a study of a medical text analysis algorithm for mortality prediction that used big data in the form of unstructured medical notes. The article describes the concept of using text mining technology for medical systems, a method for preprocessing medical data to predict patient mortality, an algorithm for predicting patient deaths based on the logistic regression classifier and presents a software module for implementing the proposed algorithm.