{"title":"机器学习在心脏病学和心脏外科风险评估评分中的应用","authors":"Suyog Mokashi, Martin Keane","doi":"10.1177/26324636241258265","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) has attracted great interest in the world of cardiology and cardiovascular surgery. For simplicity, AI has 3 distinct sectors: machine learning (ML), deep learning, and generative AI. In the case of ML, when calculating cardiovascular risk scores, ML algorithms analyze large, complex datasets (data mining) to predict the risk of morbidity and mortality.","PeriodicalId":429933,"journal":{"name":"Indian Journal of Clinical Cardiology","volume":"134 42","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Utility of Machine Learning for Cardiology and Cardiac Surgery Risk Assessment Scores\",\"authors\":\"Suyog Mokashi, Martin Keane\",\"doi\":\"10.1177/26324636241258265\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial intelligence (AI) has attracted great interest in the world of cardiology and cardiovascular surgery. For simplicity, AI has 3 distinct sectors: machine learning (ML), deep learning, and generative AI. In the case of ML, when calculating cardiovascular risk scores, ML algorithms analyze large, complex datasets (data mining) to predict the risk of morbidity and mortality.\",\"PeriodicalId\":429933,\"journal\":{\"name\":\"Indian Journal of Clinical Cardiology\",\"volume\":\"134 42\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Indian Journal of Clinical Cardiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/26324636241258265\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Clinical Cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/26324636241258265","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Utility of Machine Learning for Cardiology and Cardiac Surgery Risk Assessment Scores
Artificial intelligence (AI) has attracted great interest in the world of cardiology and cardiovascular surgery. For simplicity, AI has 3 distinct sectors: machine learning (ML), deep learning, and generative AI. In the case of ML, when calculating cardiovascular risk scores, ML algorithms analyze large, complex datasets (data mining) to predict the risk of morbidity and mortality.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
