Derin öğrenme kullanılarak elektrokardiyogramlarda kardiyak aritmilerin tespiti

Machine learning algorithms, often known as machine learning, are used by medical diagnostic support systems to boost efficiency, accuracy, and turnaround time in patient care. Many modern medical monitoring tools have their roots in recent advancements in embedded machine learning applications. The latter have sensors for measuring biological signals in order to track the functioning of a specific organ in a subject. The primary purpose of these instruments is to gather signals, store them, and then analyze them so that a correct diagnosis may be made, or at least the symptoms of any underlying pathology can be identified. Within this framework, the work presented in this paper seeks to adopt novel methodologies for the analysis and diagnosis of Electrocardiogram (ECG) signals, with a particular emphasis on the detection of cardiac arrhythmia episodes.