Use of artificial intelligence to identify cardiovascular compromise in a model of hemorrhagic shock

Critical Care Medicine

Volumn 32, Issue 2, 2004, Pages 450-456

  Glass, Todd F ^a   Knapp, Jason ^b,c   Amburn, Philip ^d   Clay, Bruce A ^e   Kabrisky, Matt ^b   Rogers, Steven K ^b   Garcia, Victor F ^a  

^a CINCINNATI CHILDREN'S HOSPITAL MEDICAL CENTER   (United States)

^b CADx Systems   (United States)

^c Wright State University   (United States)

^d SCIENCE APPLICATIONS INTERNATIONAL CORPORATION   (United States)

^e NONE

Author keywords

Artificial intelligence; Cardiovascular; Hemorrhage; Monitoring; Shock; Trauma

Indexed keywords

GLUCOSE;

ACCURACY; ANESTHESIA; ANIMAL MODEL; ARTICLE; ARTIFICIAL INTELLIGENCE; BLOOD GAS ANALYSIS; BLOOD PRESSURE MONITORING; BLOOD SAMPLING; BLOOD VOLUME; CARDIOVASCULAR DISEASE; CAUSE OF DEATH; COMPUTER PROGRAM; CONTROLLED STUDY; CORE TEMPERATURE; ELECTROCARDIOGRAM; ELECTROCARDIOGRAPHY; ELECTROENCEPHALOGRAM; END TIDAL CARBON DIOXIDE TENSION; FEMALE; HEART OUTPUT; HEMORRHAGIC SHOCK; LUNG ARTERY PRESSURE; MALE; MEAN ARTERIAL PRESSURE; NONHUMAN; OXYGEN SATURATION; PRIORITY JOURNAL; PULSE OXIMETRY; QRS COMPLEX; RR INTERVAL; SPLENECTOMY; SWINE; VENOUS OXYGEN TENSION; VENOUS PRESSURE;

ANIMALS; ARTIFICIAL INTELLIGENCE; CARDIOVASCULAR DISEASES; DISEASE MODELS, ANIMAL; FEMALE; MALE; PROSPECTIVE STUDIES; SHOCK, HEMORRHAGIC; SWINE;

EID: 1242300089     PISSN: 00903493     EISSN: None     Source Type: Journal    
DOI: 10.1097/01.CCM.0000109444.02324.AD     Document Type: Article

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