Bayesian probabilistic network modeling of remifentanil and propofol interaction on wakeup time after closed-loop controlled anesthesia

Journal of Clinical Monitoring and Computing

Volumn 17, Issue 1, 2002, Pages 31-36

  Bothner, Ulrich ^a   Milne, Stewart E ^b   Kenny, Gavin N C ^b   Georgieff, Michael ^a   Schraag, Stefan ^a  

^a UNIVERSITY OF ULM   (Germany)

^b GLASGOW ROYAL INFIRMARY   (United Kingdom)

Author keywords

Bayesian analysis; Closed loop anesthesia; Knowledge engineering; Pharmacokinetic modeling; Probabilistic belief networks; Target controlled infusion

Indexed keywords

ANESTHESIOLOGY; COMPUTATIONAL METHODS; COMPUTER SOFTWARE; PHARMACODYNAMICS; PROBABILITY DISTRIBUTIONS; SURGERY;

BAYESIAN PROBABILISTIC NETWORK;

ANESTHETICS;

PROPOFOL; REMIFENTANIL; INTRAVENOUS ANESTHETIC AGENT; PIPERIDINE DERIVATIVE;

ACCURACY; ALGORITHM; ANESTHESIA; ANESTHESIA LEVEL; ANESTHETIC RECOVERY; ARTICLE; BAYES THEOREM; BIOMEDICAL ENGINEERING; COMPUTER GRAPHICS; COMPUTER NETWORK; COMPUTER PROGRAM; COMPUTER SIMULATION; CONCENTRATION (PARAMETERS); CONTROLLED DRUG RELEASE; CONTROLLED STUDY; DRUG DISTRIBUTION; EVOKED AUDITORY RESPONSE; EYE MOVEMENT; FEEDBACK SYSTEM; FREQUENCY ANALYSIS; HUMAN; LINEAR SYSTEM; MAJOR CLINICAL STUDY; MICROCOMPUTER; PHARMACODYNAMICS; PREDICTION; PRIORITY JOURNAL; PROBABILITY; RANDOMIZATION; SAMPLING; STATISTICAL MODEL; STOCHASTIC MODEL; TIME; VALIDATION PROCESS; WAKEFULNESS; INHALATION ANESTHESIA;

ANESTHESIA RECOVERY PERIOD; ANESTHESIA, CLOSED-CIRCUIT; ANESTHETICS, INTRAVENOUS; BAYES THEOREM; HUMANS; PIPERIDINES; PROPOFOL;

EID: 0036046991     PISSN: 13871307     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1015492919566     Document Type: Article

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