Diagnostic assessment of a deep learning system for detecting atrial fibrillation in pulse waveforms

Heart

Volumn 104, Issue 23, 2018, Pages 1921-1928

  Poh, Ming Zher ^a   Poh, Yukkee Cheung ^a   Chan, Pak Hei ^b   Wong, Chun Ka ^b   Pun, Louise ^c   Leung, Wangie Wan Chiu ^c   Wong, Yu Fai ^c   Wong, Michelle Man Ying ^c   Chu, Daniel Wai Sing ^c   Siu, Chung Wah ^b  

^a Cardiio Inc   (United States)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

^c HOSPITAL AUTHORITY   (Hong Kong)

Author keywords

atrial fibrillation; ehealth telemedicine mobile health; premature ventricular beats

Indexed keywords

AGED; AMBULATORY MONITORING; ATRIAL FIBRILLATION; COMPARATIVE EFFECTIVENESS; DEVICES; DIMENSIONAL MEASUREMENT ACCURACY; ELECTROCARDIOGRAPHY; FEMALE; HEART VENTRICLE EXTRASYSTOLE; HUMAN; MALE; MIDDLE AGED; PHOTOELECTRIC PLETHYSMOGRAPHY; PROCEDURES; SENSITIVITY AND SPECIFICITY; SMARTPHONE; TELEMEDICINE; VALIDATION STUDY;

AGED; ATRIAL FIBRILLATION; COMPARATIVE EFFECTIVENESS RESEARCH; DEEP LEARNING; DIMENSIONAL MEASUREMENT ACCURACY; ELECTROCARDIOGRAPHY; FEMALE; HUMANS; MALE; MIDDLE AGED; MONITORING, AMBULATORY; PHOTOPLETHYSMOGRAPHY; SENSITIVITY AND SPECIFICITY; SMARTPHONE; TELEMEDICINE; VENTRICULAR PREMATURE COMPLEXES;

EID: 85048181852     PISSN: 13556037     EISSN: 1468201X     Source Type: Journal    
DOI: 10.1136/heartjnl-2018-313147     Document Type: Article

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