The 12-lead electrocardiography (ECG) is the gold standard for diagnosis of abnormalities of the heart. However, the ECG is susceptible to artifacts, which may lead to wrong diagnosis and thus mistreatment. It is a clinical challenge of great significance differentiating ECG artifacts from patterns of diseases. We propose a computational framework, called the matrix of regularity, to evaluate the quality of ECGs. The matrix of regularity is a novel mechanism to fuse results from multiple tests of signal quality. Moreover, this method can produce a continuous grade, which can more accurately represent the quality of an ECG. When tested on a dataset from the Computing in Cardiology/PhysioNet Challenge 2011, the algorithm achieves up to 95% accuracy. The area under the receiver operating characteristic curve is 0.97. The developed framework and computer program have the potential to improve the quality of ECGs collected using conventional and portable devices.

In addition to the benefits of each drug, valsartan/HCTZ's metabolic interactions reduce some of the negative effects of both compounds. With its increased simplicity, minimal side-effect profile and efficacy without a significant cost penalty, valsartan/HCTZ represents an excellent choice for antihypertensive therapy.

No abstract

Sudden cardiac arrest (SCA) due to fatal cardiac arrhythmias such as ventricular fibrillation is the leading cause of death in the United States, killing 350,000 Americans each year. Thus, it is of great importance to investigate the mechanisms that can suppress abnormal heart rhythms. In this work, we study the effects of drugs such as channel blockers through mathematical modeling of cardiac electrophysiological phenomena. In particular, we carry out multi-level simulations to study how channel blockers affect arrhythmias at cellular, fiber, and tissue levels. Numerical simulations show that the drugs have different effects at different scales (cellular versus fiber or tissue). Moreover, the drugs may appear to be arrhythmic in one model but antiarrhythmic in another. These observations indicate that analysis and simulation based on multiple scales and multiple models are crucial to fully understand the properties of drugs in treating arrhythmias.