Predicting cardiovascular disease from real-time electrocardiographic monitoring: An adaptive machine learning approach on a cell phone

Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Volumn , Issue , 2009, Pages 6889-6892

  Jin, Zhanpeng ^a   Sun, Yuwen ^a   Cheng, Allen C ^a  

^a University of Pittsburgh   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CARDIOLOGY; CELLULAR TELEPHONES; CLASSIFICATION (OF INFORMATION); DEEP NEURAL NETWORKS; DISEASES; ELECTROCARDIOGRAPHY; FEATURE EXTRACTION; HEART; LEARNING SYSTEMS; MHEALTH; MOBILE PHONES; NEURAL NETWORKS; TELECOMMUNICATION EQUIPMENT; TELEPHONE SETS;

ADAPTIVE ARTIFICIAL NEURAL NETWORKS; ADAPTIVE MACHINE LEARNING; CARDIOVASCULAR DISEASE; ECG FEATURE EXTRACTIONS; ELECTRICAL ACTIVITIES; MACHINE LEARNING TECHNIQUES; PHYSIOLOGICAL CONDITION; REAL TIME MONITORING;

CELLULAR TELEPHONE SYSTEMS;

EID: 77951017492     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2009.5333610     Document Type: Conference Paper

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