{"title":"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","authors":"V. Mokin, O. Kovalchuk, Nadiia O. Muzyka","doi":"10.1109/ELNANO54667.2022.9927026","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":178034,"journal":{"name":"2022 IEEE 41st International Conference on Electronics and Nanotechnology (ELNANO)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligent Technology for Predicting the Risk of Patient's Death from Coronavirus Based on PRINCIPLE-Methodology for Selecting Indicators Collected from Medical Devices\",\"authors\":\"V. Mokin, O. Kovalchuk, Nadiia O. Muzyka\",\"doi\":\"10.1109/ELNANO54667.2022.9927026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":178034,\"journal\":{\"name\":\"2022 IEEE 41st International Conference on Electronics and Nanotechnology (ELNANO)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 41st International Conference on Electronics and Nanotechnology (ELNANO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELNANO54667.2022.9927026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 41st International Conference on Electronics and Nanotechnology (ELNANO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELNANO54667.2022.9927026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.