Clinical Application Of Computational Mechanics To The Cardiovascular System


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Clinical Application of Computational Mechanics to the Cardiovascular System


Clinical Application of Computational Mechanics to the Cardiovascular System

Author: T. Yamaguchi

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-06-29


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Vascular diseases, particularly atherosclerosis, are the most frequent and critical underlying fatal disorders in the industrialized world. Cardiovascular deaths are the leading cause of death in the Western world. Although cancer or malignant neoplasms recently have topped the list of causes of deaths in Japan, cardiovascular and cerebrovascular diseases bring about more deaths than cancer if they are reclassified into a unified category of diseases of the vascular system. The National Cardiovascular Center was established by the Ministry of Health and Welfare of Japan to combat cardiovascular and cerebrovascular diseases. Since the Center was opened, we have continued to support basic and clinical sturlies of cardiovascular and cerebrovascular diseases within as weil as outside the Center. Clinical studies that we have supported in modern diagnostic and therapeutic measures against cardio- and cerebrovascular diseases have made remarkable advances in recent years, especially in medical imaging technology including CT and MRI, and in interventional measures including balloon angioplasty and other catheter-based treatments. We are proud of the significant improvement in the overall survival rate and the quality of life of patients suffering from vascular disorders. However, there are still many essential difficulties remaining in the diagnosis and treatment of vascular disorders. Such difficulties necessitate further fundamental studies not only from the practical aspect but also from the integrated perspectives of medicine, biology, and engineering.

Computational Science – ICCS 2018


Computational Science – ICCS 2018

Author: Yong Shi

language: en

Publisher: Springer

Release Date: 2018-06-11


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The three-volume set LNCS 10860, 10861 + 10862 constitutes the proceedings of the 18th International Conference on Computational Science, ICCS 2018, held in Wuxi, China, in June 2018. The total of 155 full and 66 short papers presented in this book set was carefully reviewed and selected from 404 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging ManYcore Systems; Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Data, Modeling, and Computation in IoT and Smart Systems; Track of Data-Driven Computational Sciences; Track of Mathematical-Methods-and-Algorithms for Extreme Scale; Track of Multiscale Modelling and Simulation Part III: Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Papers

Cardiovascular Computing—Methodologies and Clinical Applications


Cardiovascular Computing—Methodologies and Clinical Applications

Author: Spyretta Golemati

language: en

Publisher: Springer

Release Date: 2019-02-12


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This book provides a comprehensive guide to the state-of-the-art in cardiovascular computing and highlights novel directions and challenges in this constantly evolving multidisciplinary field. The topics covered span a wide range of methods and clinical applications of cardiovascular computing, including advanced technologies for the acquisition and analysis of signals and images, cardiovascular informatics, and mathematical and computational modeling.