{"title":"人工智能、脑电图和重症监护病房的临床结果","authors":"M. Desai","doi":"10.1109/spmb55497.2022.10014955","DOIUrl":null,"url":null,"abstract":"In this talk, we will discuss the use of electroencephalograms (EEG) in Intensive Care Units (ICU). We will review the use of EEGs as a multi-dimensional biomarker. We will review applications of artificial intelligence (AI) and machine learning (ML) for each type of biomarker. We will review cases highlighting biomarker usage in clinical management. Continuous EEG (CEEG) is an invaluable tool in the ICU since it yields multi-multi-dimensional biomarkers. AI can overcome or ameliorate limitations of CEEG applications in the ICU. Real-time analysis and interpretation of CEEG data is essential to influence clinical decision-making and clinical outcomes. ML models and AI integration into the decision-making process provides standardization and automation. Opportunities exist for the integration of real-time annotation and AI-based decision-support to achieve better patient outcomes.","PeriodicalId":261445,"journal":{"name":"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence, EEG and Clinical Outcomes in Intensive Care Units\",\"authors\":\"M. Desai\",\"doi\":\"10.1109/spmb55497.2022.10014955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this talk, we will discuss the use of electroencephalograms (EEG) in Intensive Care Units (ICU). We will review the use of EEGs as a multi-dimensional biomarker. We will review applications of artificial intelligence (AI) and machine learning (ML) for each type of biomarker. We will review cases highlighting biomarker usage in clinical management. Continuous EEG (CEEG) is an invaluable tool in the ICU since it yields multi-multi-dimensional biomarkers. AI can overcome or ameliorate limitations of CEEG applications in the ICU. Real-time analysis and interpretation of CEEG data is essential to influence clinical decision-making and clinical outcomes. ML models and AI integration into the decision-making process provides standardization and automation. Opportunities exist for the integration of real-time annotation and AI-based decision-support to achieve better patient outcomes.\",\"PeriodicalId\":261445,\"journal\":{\"name\":\"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"volume\":\"192 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/spmb55497.2022.10014955\",\"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 Signal Processing in Medicine and Biology Symposium (SPMB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/spmb55497.2022.10014955","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial Intelligence, EEG and Clinical Outcomes in Intensive Care Units
In this talk, we will discuss the use of electroencephalograms (EEG) in Intensive Care Units (ICU). We will review the use of EEGs as a multi-dimensional biomarker. We will review applications of artificial intelligence (AI) and machine learning (ML) for each type of biomarker. We will review cases highlighting biomarker usage in clinical management. Continuous EEG (CEEG) is an invaluable tool in the ICU since it yields multi-multi-dimensional biomarkers. AI can overcome or ameliorate limitations of CEEG applications in the ICU. Real-time analysis and interpretation of CEEG data is essential to influence clinical decision-making and clinical outcomes. ML models and AI integration into the decision-making process provides standardization and automation. Opportunities exist for the integration of real-time annotation and AI-based decision-support to achieve better patient outcomes.