基于原理的冠状病毒死亡风险智能预测技术——选取医疗器械采集指标的方法

V. Mokin, O. Kovalchuk, Nadiia O. Muzyka
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引用次数: 0

摘要

在乌克兰,COVID-19已造成104,106人死亡。COVID-19的多种风险因素几乎已经确定。开发了用于选择使用医疗设备的患者筛查指标的新原理方法。这种方法的名称是选择指标标准的首字母缩略词:“可证明性”,“再现性”,“信息性”,“数值”,“临床”,“重要性”,“患病率”,“肺”,“心电图”。开发了基于贝叶斯网络的工具,根据这些指标预测患者死亡率的高风险。本文给出了一个应用所提出的方法、构建模型和形成结论的例子,这些数据由22个特征组成,来自文尼西亚医院诊断为COVID-19的280名活着的成年人和140名死亡患者。为新冠肺炎住院患者建设的临床决策工具提供了一种改进的生物医学指标和医学诊断数据处理和分析方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Technology for Predicting the Risk of Patient's Death from Coronavirus Based on PRINCIPLE-Methodology for Selecting Indicators Collected from Medical Devices
In Ukraine, COVID-19 has contributed over 104,106 deaths. Multiple risk factors for COVID-19 almost have been identified. The new PRINCIPLE methodology for selecting indicators of patient screening using medical equipment is developed. The name of this methodology is an acronym of the criteria for selecting indicators: “Provability”, “Reproducibility”, “Informativeness”, “Numerical”, “Clinical”, “Importance”, “Prevalence”, “Lungs”, “Electrocardiography”. Tools based on the Bayesian network to predict the high risk of patient mortality based on these indicators are developed. An example of application of the proposed methodology, construction of the model, and formation of conclusions by them are given for anonymized data consisting of 22 features from adults 280 alive and 140 dead patients, diagnosed with COVID-19 at the hospital in Vinnytsia. The work offers an improved method for processing and analyzing the biomedical indicators and medical diagnostic data for the clinical decision-making tool for COVID-19 inpatients construction.
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