A novel neural-inspired learning algorithm with application to clinical risk prediction

Journal of Biomedical Informatics

Volumn 54, Issue , 2015, Pages 305-314

  Tay, Darwin ^a,b   Poh, Chueh Loo ^b   Kitney, Richard I ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Cardiovascular disease; Classification; Clinical risk prediction; Neural inspired algorithms

Indexed keywords

ARTIFICIAL HEART; BLOOD; BLOOD PRESSURE; CARDIOLOGY; CELL DEATH; CLASSIFICATION (OF INFORMATION); DISEASES; EVOLUTIONARY ALGORITHMS; FORECASTING; INFRARED DEVICES; PREDICTIVE ANALYTICS; RISK PERCEPTION; SOFTWARE TESTING; STATISTICAL TESTS; SUPPORT VECTOR MACHINES;

ARTIFICIAL IMMUNE RECOGNITION SYSTEM; CARDIO-VASCULAR DISEASE; CARDIO-VASCULAR RISK FACTORS; CLINICAL RISKS; EMPIRICAL EXPERIMENTS; EXTERNAL ENVIRONMENTS; MANAGEMENT STRATEGIES; PULMONARY FUNCTION;

LEARNING ALGORITHMS;

ALGORITHM; APOPTOSIS; ARTICLE; ARTIFICIAL NEURAL CELL SYSTEM FOR CLASSIFICATION; BLOOD PRESSURE; CARDIOVASCULAR RISK; DECISION MAKING; DIETARY INTAKE; ELECTROCARDIOGRAPHY; FAMILY HISTORY; HUMAN; INFORMATION PROCESSING; LEARNING ALGORITHM; LIFESTYLE; LUNG FUNCTION; MACHINE LEARNING; NERVE CELL; NERVE CELL PLASTICITY; NERVOUS SYSTEM DEVELOPMENT; PERSONAL VALUE; PRIORITY JOURNAL; RISK ASSESSMENT; ARTIFICIAL NEURAL NETWORK; CARDIOVASCULAR DISEASE; PROCEDURES; STATISTICAL MODEL;

ALGORITHMS; CARDIOVASCULAR DISEASES; HUMANS; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); RISK ASSESSMENT;

EID: 84927962090     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2014.12.014     Document Type: Article

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