03069nam a22005175i 4500 978-981-97-8359-5 DE-He213 20251030114548.0 cr nn 008mamaa 241127s2024 si | s |||| 0|eng d 9789819783595 978-981-97-8359-5 10.1007/978-981-97-8359-5 doi RC666-701.2 MJD bicssc MED010000 bisacsh MJD thema AI Augmented ECG Technology [electronic resource] / edited by Kang-Yin Chen, Tong Liu, Hua-Yue Tao. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. VII, 140 p. 14 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Overview of AI -- Iteration and Development of ECG Devices -- Clinical Application of AI-ECG -- Limitations and Challenges of AI-ECG -- Prospects and Prospects of AI-ECG. This book mainly focuses on the application of AI technology in the field of ECG, and details the theoretical, practical, and evidence-based aspects of this technology. It extensively reviews the latest research reports, and discusses the application of artificial intelligence in the diagnosis and treatment of cardiovascular diseases. This book focuses on the application of artificial intelligence in the diagnosis and treatment of cardiovascular diseases, and discusses in depth its clinical application in the diagnosis and treatment of coronary heart disease, heart failure, arrhythmia, cardiac pacing, hypertension, myocardial disease, heart valve disease, electrolyte disorders, and other diseases. It not only provides an overview of medical artificial intelligence but also richly demonstrates its clinical practice, which will help cardiovascular doctors, electrocardiogram diagnostic doctors, or medical students to understand the basic theories, applications, and development direction of this field. Cardiology. 75410 Artificial intelligence. 58441 Cardiology. 75410 Artificial Intelligence. 58441 Chen, Kang-Yin. editor. edt http://id.loc.gov/vocabulary/relators/edt 88154 Liu, Tong. editor. edt http://id.loc.gov/vocabulary/relators/edt 88155 Tao, Hua-Yue. editor. edt http://id.loc.gov/vocabulary/relators/edt 88156 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819783588 Printed edition: 9789819783601 Printed edition: 9789819783618 https://doi.org/10.1007/978-981-97-8359-5 ZDB-2-SME ZDB-2-SXM 65263 65263