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Article

Big Data Clustering in Cardeology Based on Modeling of Electrical Dynamics of the Heart in the form of Fermi-Pasta-Ulam Auto-Recurrence as a New Tool for the Study of Cardiac Activity

Shmid A., Новопашин М. А., Березин А. А., Zimina E.

The mass application of mobile cardiographs already leads to both explosive quantitative growth of the number of patients available for ECG study, registered daily outside the hospital (Big DATA in cardiology), and to the emergence of new qualitative opportunities for the study of long-term oscillatory processes (weeks, months, years) of the dynamics of the individual state of the Cardiovascular system of any patient.

The article demonstrates that new opportunities of long - term continuous monitoring of the Cardiov ascular system state of patients ' mass allow to reveal the regularities (DATA MINING) of Cardiovascular system dynamics, leading to the hypothesis of the existence of an adequate Cardiovascular system model as a distributed nonlinearself - oscillating system of the FPU recurrence model class [1]. The presence of a meaningful mathematical model of Cardiovascular system within the framework of the FPU auto – recurrence [2], as a refinement of the traditional model of studying black box, further allows us to offer new computational methods for ECG analysis and prediction of Cardiovascular system dynamics for a refined diagnosis and evaluation of the effectiveness of the treatment.