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Atrial Fibrillation - Diagnosis and Management in the 21st Century provides the most up-to-date information about the most common cardiac arrhythmia in humans, atrial fibrillation. In this rapidly developing field of medicine, the book helps to answer the question, "Which treatment should I choose for which patient?" The book also discusses new drugs, applications and interventions in the field. The 12 chapters are written from a variety of viewpoints by authors who use solid, scientific and contemporary approaches to practical questions.

Atrial fibrillation. --- Atrial flutter.

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Atrial Fibrillation - Diagnosis and Management in the 21st Century provides the most up-to-date information about the most common cardiac arrhythmia in humans, atrial fibrillation. In this rapidly developing field of medicine, the book helps to answer the question, "Which treatment should I choose for which patient?" The book also discusses new drugs, applications and interventions in the field. The 12 chapters are written from a variety of viewpoints by authors who use solid, scientific and contemporary approaches to practical questions.

Atrial fibrillation --- Treatment. --- Auricular fibrillation --- Atrial arrhythmias

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The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate.

Electrical engineering --- Vorhofflimmern --- Fibrose --- maschinelles Lernen --- Bidomain --- Modellierung des Herzens --- atrial fibrillation --- fibrosis --- machine learning --- bidomain --- cardiac modeling --- Vorhofflimmern --- Fibrose --- maschinelles Lernen --- Bidomain --- Modellierung des Herzens --- atrial fibrillation --- fibrosis --- machine learning --- bidomain --- cardiac modeling

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Recent advances in information technology have brought forth a paradigm shift in science, especially in the biology and medical fields. Statistical methodologies based on high-performance computing and big data analysis are now indispensable for the qualitative and quantitative understanding of experimental results. In fact, the last few decades have witnessed drastic improvements in high-throughput experiments in health science, for example, mass spectrometry, DNA microarray, next generation sequencing, etc. Those methods have been providing massive data involving four major branches of omics (genomics, transcriptomics, proteomics, and metabolomics). Information about amino acid sequences, protein structures, and molecular structures are fundamental data for the prediction of bioactivity of chemical compounds when screening drugs. On the other hand, cell imaging, clinical imaging, and personal healthcare devices are also providing important data concerning the human body and disease. In parallel, various methods of mathematical modelling such as machine learning have developed rapidly. All of these types of data can be utilized in computational approaches to understand disease mechanisms, diagnosis, prognosis, drug discovery, drug repositioning, disease biomarkers, driver mutations, copy number variations, disease pathways, and much more. In this Special Issue, we have published 8 excellent papers dedicated to a variety of computational problems in the biomedical field from the genomic level to the whole-person physiological level.

Technology: general issues --- History of engineering & technology --- water temperature --- bathing --- ECG --- heart rate variability --- quantitative analysis --- t-test --- hypertrophic cardiomyopathy --- data mining --- automated curation --- molecular mechanisms --- atrial fibrillation --- sudden cardiac death --- heart failure --- left ventricular outflow tract obstruction --- cardiac fibrosis --- myocardial ischemia --- compound–protein interaction --- Jamu --- machine learning --- drug discovery --- herbal medicine --- data augmentation --- deep learning --- ECG quality assessment --- drug–target interactions --- protein–protein interactions --- chronic diseases --- drug repurposing --- maximum flow --- adenosine methylation --- m6A --- RNA modification --- neuronal development --- genetic variation --- copy number variants --- disease-related traits --- sequential order --- association test --- blood pressure --- cuffless measurement --- longitudinal experiment --- plethysmograph --- nonlinear regression --- n/a --- compound-protein interaction --- drug-target interactions --- protein-protein interactions

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Cardiovascular disease (CVD), including coronary artery disease, heart disease, arrhythmias, and other types of vascular diseases, is one of the leading causes of death around the world. It is estimated that approximately half of the variabilities of CVD appear to be attributed to genetics. Therefore, the other half of them have been attributed to acquired factors, including diet. It is of note that even a genetic predisposition to CVD can be canceled out by a healthy lifestyle. In this regard, it is important to acknowledge that acquired factors, including diet, are causally associated with CVD. Based on these facts, important papers are presented in this Special Issue entitled “The Effect of Diet on Cardiovascular Disease, Heart Disease, and Blood Vessels”.

Humanities --- Social interaction --- n-3 polyunsaturated fatty acids --- cardiovascular risk estimates --- cardiovascular diseases --- biomarkers --- cardiovascular risk factors --- fish --- n-3 polyunsaturated fatty acid --- cardiovascular disease mortality --- meta-analysis --- prospective cohort studies --- body mass index --- obesity --- underweight --- ischemic stroke --- hemorrhagic stroke --- high-density lipoprotein (HDL) --- cholesterol uptake capacity (CUC) --- phospholipids (PL) --- trans-fatty acids (TFA) --- elaidic acid --- lecithin-cholesterol acyltransferase (LCAT) --- aortic stiffness --- fructose --- glucose --- hypertension --- left ventricular diastolic dysfunction --- pulse wave velocity --- renal resistive index --- cardiovascular health --- atrial fibrillation --- Japanese --- sarcopenia --- heart failure --- trimethylamine-N-oxide --- inflammatory mediators --- choline --- L-carnitine --- n/a