An investigation of patterns in hemodynamic data indicative of impending hypotension in intensive care

BioMedical Engineering Online

Volumn 9, Issue , 2010, Pages

  Lee, Joon ^a,b   Mark, Roger G ^a,b  

^a HARVARD MIT DIVISION OF HEALTH SCIENCES AND TECHNOLOGY   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AREA UNDER ROCS; ARTIFICIAL NEURAL NETWORKS; BINARY CLASSIFICATION; CARDIAC OUTPUT; CLINICAL STAFF; CLINICAL VALUE; HEART RATES; INTENSIVE CARE; MACHINE-LEARNING; MEAN ABSOLUTE ERROR; MEAN ARTERIAL BLOOD PRESSURES; MEAN ARTERIAL PRESSURE; OBSERVATION PERIOD; PATTERN RECOGNITION ALGORITHMS; POSITIVE PREDICTIVE VALUES; PULSE PRESSURE; RECOGNITION PERFORMANCE;

BLOOD; BLOOD PRESSURE; HEMODYNAMICS; HYDRODYNAMICS; NEURAL NETWORKS; PATTERN RECOGNITION; TIME SERIES;

INTENSIVE CARE UNITS;

ARTICLE; AUTOMATED PATTERN RECOGNITION; HEMODYNAMICS; HUMAN; HYPOTENSION; INTENSIVE CARE; METHODOLOGY; PATHOPHYSIOLOGY; REGRESSION ANALYSIS; STATISTICAL ANALYSIS;

DATA INTERPRETATION, STATISTICAL; HEMODYNAMICS; HUMANS; HYPOTENSION; INTENSIVE CARE; PATTERN RECOGNITION, AUTOMATED; REGRESSION ANALYSIS;

EID: 77958136867     PISSN: 1475925X     EISSN: 1475925X     Source Type: Journal    
DOI: 10.1186/1475-925X-9-62     Document Type: Article

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