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008			230818s2023 sz | s |||| 0|eng d
020			_a9783031359521
024	7		_a10.1007/978-3-031-35952-1 _2doi
040			_aES-VaUEC _bspa _cES-VaUEC
050	0	4	_aTS155-194 _b2024
100	1		_aYang, Hui. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	0	0	_aSensing, Modeling and Optimization of Cardiac Systems: _bA New Generation of Digital Twin for Heart Health Informatics _cby Hui Yang, Bing Yao
250			_a1st ed 2023
264		1	_aCham _c2023 _bSpringer International Publishing
300	0	0	_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aSpringerBriefs in Service Science, _x2731-3751
520			_aThis book reviews the development of physics-based modeling and sensor-based data fusion for optimizing medical decision making in connection with spatiotemporal cardiovascular disease processes. To improve cardiac care services and patients' quality of life, it is very important to detect heart diseases early and optimize medical decision making. This book introduces recent research advances in machine learning, physics-based modeling, and simulation optimization to fully exploit medical data and promote the data-driven and simulation-guided diagnosis and treatment of heart disease. Specifically, it focuses on three major topics: computer modeling of cardiovascular systems, physiological signal processing for disease diagnostics and prognostics, and simulation optimization in medical decision making. It provides a comprehensive overview of recent advances in personalized cardiac modeling by integrating physics-based knowledge of the cardiovascular system with machine learning and multi-source medical data. It also discusses the state-of-the-art in electrocardiogram (ECG) signal processing for the identification of disease-altered cardiac dynamics. Lastly, it introduces readers to the early steps of optimal decision making based on the integration of sensor-based learning and simulation optimization in the context of cardiac surgeries. This book will be of interest to researchers and scholars in the fields of biomedical engineering, systems engineering and operations research, as well as professionals working in the medical sciences.
830		0	_aSpringerBriefs in Service Science, _x2731-3751
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-35952-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
912			_aZDB-2-BUM
912			_aZDB-2-SXBM
942			_2lcc _cLE
988			_aSpringer_Business_2023
999			_c238638 _d238638