Mazen Megahed, U. Jain, Michael T. Leasure, Adam A. Butchy
{"title":"基于新型机器学习的12导联心电图心肌梗死定位","authors":"Mazen Megahed, U. Jain, Michael T. Leasure, Adam A. Butchy","doi":"10.1145/3386164.3389084","DOIUrl":null,"url":null,"abstract":"There are multiple modalities used to diagnose abnormalities of the heart consisting of various invasive and noninvasive tests. Patients may undergo multiple tests, progressing to more invasive methods at the expense of patient risk and cost to the pair. HEARTio, through machine learning and algorithmic processing our proprietary software, hopes to improve the accuracy of the electrocardiography: a century old technology and the most commonly performed cardiac test. It is used to diagnose heart attacks, heart rhythm problems and operates as the gateway testing for patients undergoing cardiac evaluation. Myocardial infarction, or heart attacks, affect almost 800,000 Americans yearly [7] with time to treatment being the most important factor in recovery and therapy. We show in this paper that we are able to localize and detect myocardial infarctions at an accuracy above 99% by applying our system to the PTB database.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Localization of Myocardial Infarction from 12 Lead ECG Empowered with Novel Machine Learning\",\"authors\":\"Mazen Megahed, U. Jain, Michael T. Leasure, Adam A. Butchy\",\"doi\":\"10.1145/3386164.3389084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are multiple modalities used to diagnose abnormalities of the heart consisting of various invasive and noninvasive tests. Patients may undergo multiple tests, progressing to more invasive methods at the expense of patient risk and cost to the pair. HEARTio, through machine learning and algorithmic processing our proprietary software, hopes to improve the accuracy of the electrocardiography: a century old technology and the most commonly performed cardiac test. It is used to diagnose heart attacks, heart rhythm problems and operates as the gateway testing for patients undergoing cardiac evaluation. Myocardial infarction, or heart attacks, affect almost 800,000 Americans yearly [7] with time to treatment being the most important factor in recovery and therapy. We show in this paper that we are able to localize and detect myocardial infarctions at an accuracy above 99% by applying our system to the PTB database.\",\"PeriodicalId\":231209,\"journal\":{\"name\":\"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control\",\"volume\":\"136 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3386164.3389084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3386164.3389084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Localization of Myocardial Infarction from 12 Lead ECG Empowered with Novel Machine Learning
There are multiple modalities used to diagnose abnormalities of the heart consisting of various invasive and noninvasive tests. Patients may undergo multiple tests, progressing to more invasive methods at the expense of patient risk and cost to the pair. HEARTio, through machine learning and algorithmic processing our proprietary software, hopes to improve the accuracy of the electrocardiography: a century old technology and the most commonly performed cardiac test. It is used to diagnose heart attacks, heart rhythm problems and operates as the gateway testing for patients undergoing cardiac evaluation. Myocardial infarction, or heart attacks, affect almost 800,000 Americans yearly [7] with time to treatment being the most important factor in recovery and therapy. We show in this paper that we are able to localize and detect myocardial infarctions at an accuracy above 99% by applying our system to the PTB database.