Automatic Identification and Classification Diagnosis of Atrial Ventricular Hypertrophy Electrocardiogram Based on Convolutional Neural Network / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation
;
(6): 20-23, 2020.
Artículo
en Chino
| WPRIM
| ID: wpr-942689
ABSTRACT
OBJECTIVE@#Identifying Atrial Ventricular Hypertrophy Electrocardiogram (AVH ECG)and diagnosing the classification of theirs automatically.@*METHODS@#The ECG data used in this experiment was collected from the First Affiliated Hospital of China Medical University. CNN are combined with conventional methods and a 10 layers of one dimensional CNN are created in this experiment to extract the features of ECG signals automatically and achieve the function of classifying. ROC, sensitivity and F1-score are used here to evaluate the effects of the model.@*RESULTS@#In the experiment of identifying AVH ECG, the AUC of test dataset is 0.991, while in the experiment of classifying AVH ECG, the maximal F1-score can reach 0.992.@*CONCLUSIONS@#The CNN model created in this experiment can achieve the auxiliary diagnosis of AVH ECG.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
China
/
Redes Neurales de la Computación
/
Electrocardiografía
/
Atrios Cardíacos
/
Hipertrofia
Tipo de estudio:
Estudio diagnóstico
/
Estudio pronóstico
Límite:
Humanos
País/Región como asunto:
Asia
Idioma:
Chino
Revista:
Chinese Journal of Medical Instrumentation
Año:
2020
Tipo del documento:
Artículo
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