Use of advanced machine-learning techniques for noninvasive monitoring of hemorrhage

Journal of Trauma - Injury, Infection and Critical Care

Volumn 71, Issue SUPPL. 1, 2011, Pages

  Convertino, Victor A ^a   Moulton, Steven L ^b   Grudic, Gregory Z ^c   Rickards, Caroline A ^d   Hinojosa Laborde, Carmen ^a   Gerhardt, Robert T ^a   Blackbourne, Lorne H ^a   Ryan, Kathy L ^a  

^a US ARMY INSTITUTE OF SURGICAL RESEARCH   (United States)

^b UNIVERSITY OF COLORADO   (United States)

^c Flashback Technologies   (United States)

^d UNIVERSITY OF TEXAS AT SAN ANTONIO   (United States)

Author keywords

Lower body negative pressure; Medical monitoring; Shock

Indexed keywords

ACCURACY; ALGORITHM; BLOOD VOLUME; HEART FAILURE; HEMODYNAMIC PARAMETERS; HEMORRHAGIC SHOCK; HUMAN; MACHINE LEARNING; MEDICAL DECISION MAKING; MONITORING; NON INVASIVE PROCEDURE; PREDICTION; PRIORITY JOURNAL; REVIEW;

ALGORITHMS; BLOOD PRESSURE; BLOOD VOLUME; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; LOWER BODY NEGATIVE PRESSURE; MILITARY MEDICINE; MODELS, CARDIOVASCULAR; MONITORING, PHYSIOLOGIC; SHOCK, HEMORRHAGIC;

EID: 79960393129     PISSN: 00225282     EISSN: 15298809     Source Type: Journal    
DOI: 10.1097/TA.0b013e3182211601     Document Type: Review

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