作者: L Xu
DOI:
关键词: Simulation 、 Artificial intelligence 、 Computational model 、 Bridging (networking) 、 Experimental data 、 Machine learning 、 Cardiac electrophysiology 、 Sudden death 、 Fibrillation 、 Ventricular fibrillation 、 Mechanism (biology) 、 Engineering
摘要: Ventricular fibrillation (VF) is the leading heart rhythm for causing sudden death worldwide, claiming 70,000 deaths per year in UK alone. Understanding mechanism initiating crucial progressing future therapies and risk stratification implantable cardioverter-defibrillator therapy. Experimental studies computerized simulations of cardiac activity have significantly contributed to understanding electrophysiology. Although these been very successful at bridging gap between basic research findings arrhythmia, few made on construction an accurate simulation based patient-acquired data. There remain some distances computational modeling clinical appreciation arrhythmia generation. The primary objective this project was develop new numerical procedures carry out data referring existing models. To achieve objective, divided into three parts: first part create models electrical restitution tissue conduction model activation signal, which can be fitted with experimental obtain properties; second approach validate extra-stimuli demonstrating that prediction complex interactions time dynamics sequential premature beats; last focusing initiation functional block patient-specific main contribution work it provided a platform by incorporated served as method fundamental science bridged.