Am J Physiol Heart Circ Physiol
December 2022
Artificial intelligence algorithms are being adopted to analyze medical data, promising faster interpretation to support doctors' diagnostics. The next frontier is to bring these powerful algorithms to implantable medical devices. Herein, a closed-loop solution is proposed, where a cellular neural network is used to detect abnormal wavefronts and wavebrakes in cardiac signals recorded in human tissue is trained to achieve >96% accuracy, >92% precision, >99% specificity, and >93% sensitivity, when floating point precision weights are assumed.
View Article and Find Full Text PDFTemporary postoperative cardiac pacing requires devices with percutaneous leads and external wired power and control systems. This hardware introduces risks for infection, limitations on patient mobility, and requirements for surgical extraction procedures. Bioresorbable pacemakers mitigate some of these disadvantages, but they demand pairing with external, wired systems and secondary mechanisms for control.
View Article and Find Full Text PDFBackground: Epicardial adipose tissue (EAT) accumulation is associated with cardiac arrhythmias. The effect of EAT secretome (EATs) on cardiac electrophysiology remains largely unknown.
Objective: The purpose of this study was to investigate the arrhythmogenicity of EATs and its underlying molecular and electrophysiological mechanisms.