Research and implementation of the medical text analysis algorithm for predicting mortality

Q2 Mathematics
Zhenisgul Rakhmetullina, Saule Belginova, Alibekkyzy Karlygash, Aigerim Ismukhamedova, Shynar Tezekpaeva
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引用次数: 0

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.
研究和实施预测死亡率的医学文本分析算法
死亡率预测在制定医疗质量的描述性衡量标准方面可以发挥作用,它为比较和评估医院提供了一种公平公正的方法。本文介绍了一项针对死亡率预测的医学文本分析算法的研究,该算法使用了非结构化医疗笔记形式的大数据。文章介绍了在医疗系统中使用文本挖掘技术的概念、预处理医疗数据以预测患者死亡率的方法、基于逻辑回归分类器预测患者死亡的算法,并介绍了实现所提算法的软件模块。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.90
自引率
0.00%
发文量
782
期刊介绍: The aim of Indonesian Journal of Electrical Engineering and Computer Science (formerly TELKOMNIKA Indonesian Journal of Electrical Engineering) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the applications of Telecommunication and Information Technology, Applied Computing and Computer, Instrumentation and Control, Electrical (Power), Electronics Engineering and Informatics which covers, but not limited to, the following scope: Signal Processing[...] Electronics[...] Electrical[...] Telecommunication[...] Instrumentation & Control[...] Computing and Informatics[...]
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