National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Deep-learning based localization of cardiac arrhythimas in ECG
Khaliullina, Sabina ; Novotná, Petra (referee) ; Ronzhina, Marina (advisor)
The thesis deals with the localization and classification of atrial atrial fibrillation. In Python, a detection method using convolutional neural networks with multi-instance learning (MIL) and the method of local maxima for localization were implemented. Segments from two ECG leads were used. In the binary classification using the first subset and subsequent post processing, the F1 score reached 100 %, in the classification using the second subset 92 %. In the discussion and conclusion of the work, the success of classification and localization was evaluated, the achieved results were discussed and compared the with the results of other authors.
Deep-learning based localization of cardiac arrhythimas in ECG
Khaliullina, Sabina ; Novotná, Petra (referee) ; Ronzhina, Marina (advisor)
The thesis deals with the localization and classification of atrial atrial fibrillation. In Python, a detection method using convolutional neural networks with multi-instance learning (MIL) and the method of local maxima for localization were implemented. Segments from two ECG leads were used. In the binary classification using the first subset and subsequent post processing, the F1 score reached 100 %, in the classification using the second subset 92 %. In the discussion and conclusion of the work, the success of classification and localization was evaluated, the achieved results were discussed and compared the with the results of other authors.

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