Fully-Automated Diagnosis of Aortic Stenosis Using Phonocardiogram-Based Features.
Annu Int Conf IEEE Eng Med Biol Soc
; 2019: 6673-6676, 2019 Jul.
Article
em En
| MEDLINE
| ID: mdl-31947372
The irreversible damage and eventual heart failure caused by untreated aortic stenosis (AS) can be prevented by early detection and timely intervention. Prior work in the field of phonocardiogram (PCG) signal analysis has provided proof of concept for using heart-sound data in AS diagnosis. However, such systems either require operation by trained technicians, fail to address a diverse subject set, or involve unwieldy configuration procedures that challenge real-world application. This paper presents an end-to-end, fully-automated system that uses noise-subtraction, heartbeat-segmentation and quality-assurance algorithms to extract physiologically-motivated features from PCG signals to diagnose AS. When tested on n=96 patients showing a diverse set of cardiac and non-cardiac conditions, the system was able to diagnose AS with 92% sensitivity and 95% specificity.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Estenose da Valva Aórtica
/
Ruídos Cardíacos
Tipo de estudo:
Diagnostic_studies
/
Screening_studies
Limite:
Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Ano de publicação:
2019
Tipo de documento:
Article
País de publicação:
Estados Unidos