Classification method of atrial fibrillation and congestive heart failure using a convolutional artificial neural network

Provided is a method for classifying the atrial fibrillation (AF) and congestive heart failure (CHF) using neural networks. Through a one-dimensional convolutional neural network (1-D CNN), based on raw electrocardiogram (ECG) signals, AF, CHF, and normal sinus rhythm (NSR) are classified. 신경망을 이용한...

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Bibliographische Detailangaben
Hauptverfasser:	YOO YE DAM, YUNENDAH NUR FUADAH, JEONG DA UN, LIM KI MOO
Format:	Patent
Sprache:	eng ; kor
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DIAGNOSIS HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA HUMAN NECESSITIES HYGIENE IDENTIFICATION INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEDICAL OR VETERINARY SCIENCE PHYSICS SURGERY
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Beschreibung
Zusammenfassung:	Provided is a method for classifying the atrial fibrillation (AF) and congestive heart failure (CHF) using neural networks. Through a one-dimensional convolutional neural network (1-D CNN), based on raw electrocardiogram (ECG) signals, AF, CHF, and normal sinus rhythm (NSR) are classified. 신경망을 이용한 심방세동과 울혈성 심부전의 분류방법은 1차원 컨볼루션 신경망(1-D CNN)을 통해 원시 심전도(Electrocardiogram, ECG) 신호를 기반으로 심방세동 (atrial fibrillation, AF), 울혈성 심부전(Congestive heart failure , CHF) 및 정상 부비동 리듬(Normal Sinus Rhythm, NSR)을 각각 분류하는 것을 특징으로 한다.