Greedy based convolutional neural network optimization for detecting apnea

•The proposed method requires less computation time to optimize CNN's structure for patient detection.•The best CNNs acquires through our proposed method detects apnea epochs and patient with strong accuracy.•Cross-database classification and transfer learning are viable in the proposed network...

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Veröffentlicht in:	Computer methods and programs in biomedicine 2020-12, Vol.197, p.105640-105640, Article 105640
Hauptverfasser:	Mostafa, Sheikh Shanawaz, Baptista, Darío, Ravelo-García, Antonio G., Juliá-Serdá, Gabriel, Morgado-Dias, Fernando
Format:	Artikel
Sprache:	eng
Schlagworte:	Classification algorithms, sleep apnea CNN Databases, Factual Electrocardiography Humans Hyperparameter Neural Networks, Computer Optimization Polysomnography Sleep Apnea Syndromes - diagnosis
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