Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns

Journal of Biomedical Informatics

Volumn 66, Issue , 2017, Pages 19-31

  Ghosh, Shameek ^a   Li, Jinyan ^a   Cao, Longbing ^a   Ramamohanarao, Kotagiri ^b  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

^b UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

Coupled hidden Markov models; Septic shock; Sequential pattern mining; Symbolic sequences

Indexed keywords

BLOOD PRESSURE; CONTINUOUS TIME SYSTEMS; FORECASTING; HEART; INTENSIVE CARE UNITS; LEARNING SYSTEMS; MARKOV PROCESSES; PATIENT MONITORING; PHYSIOLOGICAL MODELS; PHYSIOLOGY;

COUPLED HIDDEN MARKOV MODELS; MACHINE LEARNING APPROACHES; MEAN ARTERIAL PRESSURE; MULTIPLE ORGAN FAILURE; PHYSIOLOGICAL CONDITION; SEPTIC SHOCKS; SEQUENTIAL-PATTERN MINING; SYMBOLIC SEQUENCE;

HIDDEN MARKOV MODELS;

ARTICLE; BREATHING RATE; COMPUTER PREDICTION; CONTROLLED STUDY; HEART RATE; HIDDEN MARKOV MODEL; HUMAN; INFECTION RISK; INTENSIVE CARE; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MEAN ARTERIAL PRESSURE; PATIENT CARE; PREDICTIVE VALUE; PRIORITY JOURNAL; RISK ASSESSMENT; SEPTIC SHOCK; SEQUENTIAL ANALYSIS; SUPPORT VECTOR MACHINE; VALIDATION PROCESS; VALIDATION STUDY; BLOOD PRESSURE; FORECASTING; INTENSIVE CARE UNIT; MACHINE LEARNING; MULTIPLE ORGAN FAILURE; PROCEDURES;

BLOOD PRESSURE; CRITICAL CARE; FORECASTING; HEART RATE; HUMANS; INTENSIVE CARE UNITS; MACHINE LEARNING; MULTIPLE ORGAN FAILURE; RISK ASSESSMENT; SHOCK, SEPTIC;

EID: 85007438910     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2016.12.010     Document Type: Article

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