Atrial fibrillation (AF) is one of the most common arrhythmias. Today, there are a large number of AF patients worldwide, and incidence increases with the increase of age. However, the current diagnosis rate of AF via auxiliary examination is relatively low. In view of the widespread application of artificial intelligence (AI) in the medical field, the diagnosis of AF using AI has also become a research hotspot. This article briefly introduces the relevant aspects of AI and reviews the application of AI in AF prediction.
Atrial fibrillation is one of the most common arrhythmia. Cardiac mapping technology, an important method to study the electrophysiological mechanism of atrial fibrillation, can determine the abnormal origin and record the distribution and transmission way of these atrial electrical signals. This technology offers a new way for research the electrophysiological mechanism of atrial fibrillation. The purpose of this study is to review the research progress of cardiac mapping in the electrophysiological mechanism of atrial fibrillation and clinical application.
The capacity for self-regeneration of the adult heart is very limited, conventional therapies cannot solve the loss of cardiomyocytes in the infarcted heart leads to continuous ventricular remodeling. Cell transplantation therapy is emerging as a novel approach for myocardial repair over conventional therapies. Various types of cell transplantation have improved cardiac function and angiogenesis in animal models and clinical settings. The safety and feasibility of some clinical trials have been initiated. In this review, we summarize the advantages and limitations of different cell types proposed for cell transplantation in myocardial infarction and give an overview of the clinical trials using this novel therapeutic approach in patients with myocardial infarction.
