EAN: 9783031359514

SPRINGERBRIEFS IN SERVICE SCIENCE SENSING MOD...

This 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.

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