{"title":"[Artificial intelligence-enhanced electrocardiography : Will it revolutionize diagnosis and management of our patients?]","authors":"Wilhelm Haverkamp, Nils Strodthoff","doi":"10.1007/s00399-024-00997-0","DOIUrl":null,"url":null,"abstract":"<p><p>The use of artificial intelligence (AI) in healthcare has made significant progress in the last 10 years. Many experts believe that utilization of AI technologies, especially deep learning, will bring about drastic changes in how physicians understand, diagnose, and treat diseases. One aspect of this development is AI-enhanced electrocardiography (ECG) analysis. It involves not only optimizing the traditional ECG analysis by the physician and improving the accuracy of automatic interpretation by the ECG device but also introducing entirely new diagnostic options enabled by AI. Examples include assessing left ventricular function, predicting atrial fibrillation, and diagnosing both cardiac and noncardiac conditions. Through AI, the ECG becomes a comprehensive tool for screening, diagnosis, and patient management, potentially revolutionizing clinical practices. This paper provides an overview of the current state of this development, discusses existing limitations, and explores the challenges that may arise for healthcare professionals in this context.</p>","PeriodicalId":52403,"journal":{"name":"Herzschrittmachertherapie und Elektrophysiologie","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Herzschrittmachertherapie und Elektrophysiologie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s00399-024-00997-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/15 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
The use of artificial intelligence (AI) in healthcare has made significant progress in the last 10 years. Many experts believe that utilization of AI technologies, especially deep learning, will bring about drastic changes in how physicians understand, diagnose, and treat diseases. One aspect of this development is AI-enhanced electrocardiography (ECG) analysis. It involves not only optimizing the traditional ECG analysis by the physician and improving the accuracy of automatic interpretation by the ECG device but also introducing entirely new diagnostic options enabled by AI. Examples include assessing left ventricular function, predicting atrial fibrillation, and diagnosing both cardiac and noncardiac conditions. Through AI, the ECG becomes a comprehensive tool for screening, diagnosis, and patient management, potentially revolutionizing clinical practices. This paper provides an overview of the current state of this development, discusses existing limitations, and explores the challenges that may arise for healthcare professionals in this context.
期刊介绍:
Mit wissenschaftlichen Original- und Übersichtsarbeiten, Berichten über moderne Operationstechniken und experimentelle Methoden ist die Zeitschrift Herzschrittmachertherapie + Elektrophysiologie ein Diskussionsforum für Themen wie:
- Zelluläre Elektrophysiologie
- Theoretische Elektrophysiologie
- Klinische Elektrophysiologie
- Angewandte Herzschrittmachertherapie
- Bradykarde und tachykarde Herzrhythmusstörungen
- Plötzlicher Herztod und Risikostratifikation
- Elektrokardiographie
- Elektromedizinische Technologie
- Experimentelle und klinische Pharmakologie
- Herzchirurgie bei Herzrhythmusstörungen
Mitteilungen der Arbeitsgruppen Herzschrittmacher und Arrhythmie der Deutschen Gesellschaft für Kardiologie - Herz und Kreislaufforschung e.V. (DGK) sowie Stellungnahmen und praktische Hinweise runden das breite Spektrum dieser Zeitschrift ab.
Interessensgebiete: Kardiologie, Herzschrittmachertherapie, Herzschrittmachertechnologie, klinische Elektrophysiologie