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Neutrosophic Sets and Systems

Abstract

Cardiac arrhythmias are cardiovascular conditions caused by irregularities in the formation or transmission of electrical impulses. To identify these arrhythmias and determine their origin, an electrocardiogram (ECG) is used, which graphically records the electrical activity responsible for each heartbeat over a short period. This analysis can reveal stochastic changes, introducing a degree of uncertainty. To detect these changes, neutrosophic control charts provide an appropriate statistical tool to assess the stability of the ECG, anticipate potential heart failures, reduce variability in measurements, and, in some cases, make predictions. The results indicate that the proposed model is highly accurate in detecting and classifying arrhythmias and that T^2 control charts are useful for monitoring the quality of the detection process. In conclusion, the proposed hybrid neutrosophic model effectively identifies and classifies cardiac arrhythmias in clinical practice.

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