Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke

Neurocomputing

Volumn 134, Issue , 2014, Pages 269-279

  Kasabov, Nikola ^a   Feigin, Valery ^a   Hou, Zeng Guang ^b   Chen, Yixiong ^b   Liang, Linda ^a   Krishnamurthi, Rita ^a   Othman, Muhaini ^a   Parmar, Priya ^a  

^a AUCKLAND UNIVERSITY OF TECHNOLOGY   (New Zealand)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Evolving connectionist systems; Personalised modelling; Spatio temporal pattern recognition; Spiking neural networks; Stroke occurrence prediction

Indexed keywords

FORECASTING; INTELLIGENT AGENTS; LEARNING SYSTEMS; PATTERN RECOGNITION;

DEVELOPMENT AND APPLICATIONS; EVOLVING CONNECTIONIST SYSTEMS; PARAMETER OPTIMISATION; PREDICTION PROBLEM; RESERVOIR SYSTEMS; SIMILAR INDIVIDUALS; SPATIOTEMPORAL PATTERNS; SPIKING NEURAL NETWORKS;

NEURAL NETWORKS;

ADULT; AGED; ARTICLE; ATMOSPHERIC PRESSURE; AUTUMN; BIOINFORMATICS; CASE STUDY; CEREBROVASCULAR ACCIDENT; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; CLINICAL FEATURE; CONTROLLED STUDY; DATA ANALYSIS; DIAGNOSIS; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DISEASE CLASSIFICATION; DYNAMIC COMPONENT; EVOLVING SPIKING NEURAL NETWORK; FEMALE; GEOGRAPHIC INFORMATION SYSTEM; HUMAN; HUMAN CELL; INFORMATION PROCESSING; MACHINE LEARNING; MALE; MATHEMATICAL MODEL; NERVE CELL NETWORK; PERSONALISED MODEL; PREDICTION; PRIORITY JOURNAL; PROCESS OPTIMIZATION; RESERVOIR; SPATIO SPECTRO TEMPORAL DATA; SPIKE WAVE; STATIC COMPONENT; SYNAPSE; TEMPERATURE; TRAINING; VERY ELDERLY; WEATHER;

EID: 84896548177     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.09.049     Document Type: Article

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