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There exists no clear method to distinguish between potentially useful or harmful drugs in the setting of excitable cardiac disease. Computational modeling, however, can be utilized to predict interactions and consequences of antiarrhythmics. One application of this approach is in exploring the mechanism of action of the antiarrhythmic drug flecainide, once condemned for causing an increased incidence of sudden cardiac death, which has been shown to demonstrate efficacy in patients with catecholaminergic polymorphic ventricular tachycardia (CPVT). In addition to its classic effects on sodium current, flecainide has been shown to interact with the ryanodine receptor. This work first gives an introduction to computer modeling, cardiac electrophysiology, and their intersection. A detailed background on CPVT then follows this introduction, including the genetic basis, experimental models, and options for treatment of CPVT. An initial study utilizes a computational approach to predict the mechanism of efficacy of the drug flecainide in the setting of CPVT. The models are then expanded upon in a second study in order to predict alternate therapy to rectify electrical abnormalities in the setting of CPVT. These two studies highlight the emerging applications of computational modeling as a tool to direct the development of novel therapeutic treatments and strategies for cardiac rhythm pathologies.
Fully updated from cover to cover, Zipes and Jalife’s Cardiac Electrophysiology: From Cell to Bedside, 8th Edition, provides the comprehensive, multidisciplinary coverage you need—from new knowledge in basic science to the latest clinical advances in the field. Drs. José Jalife and William Gregory Stevenson lead a team of global experts who provide cutting-edge content and step-by-step instructions for all aspects of cardiac electrophysiology. Packs each chapter with the latest information necessary for optimal basic research as well as patient care. Covers new technologies such as CRISPR, protein research, improved cardiac imaging, optical mapping, and wearable devices. Contains significant updates in the areas of molecular biology and genetics, iPSCs (induced pluripotent stem cells), embryonic stem cells, precision medicine, antiarrhythmic drug therapy, cardiac mapping with advanced techniques, and ablation technologies including stereotactic radioablation. Includes 47 new standalone chapters that are organized into discrete topics for improved access. Discusses extensive recent progress in the understanding, diagnosis, and management of arrhythmias, including new clinical insights on atrial fibrillation and stroke prevention, new advances in the understanding of ventricular arrythmias in genetic disease, and advances in implantable devises and infection management. Features 1,600 high-quality photographs, anatomic and radiographic images, electrocardiograms, tables, algorithms, and more., with additional figures, tables, and videos online. Recipient of a 2018 Highly Commended award from the British Medical Association.
This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
This book covers all the major aspects associated with pathophysiological development of cardiac arrhythmias (covering enhanced or suppressed automaticity, triggered activity, or re-entry), from basic concepts through disease association, limitations of current pharmacotherapy and implant therapies and on-going trials and analysis of new biomarkers based on current knowledge of cellular interaction and signalling. The book describes novel and state-of-the-art methods for differentiating between the major types of arrhythmia, structural abnormalities and current practice guidelines and determination of risk stratification associated with sudden cardiac death. A particular focus is on arrhythmias associated with atrial fibrillation and includes details of associations with cardiac disease, current detection, analysis and imaging and future perspectives.​
Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. Now, Computational Intelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also encouraging the implementation of these methods to readers' research.