Model-based diagnosis in intensive care monitoring: The YAQ approach

  • Authors:

  • Serdar Uckun;Benoit M. Dawant;Daniel P. Lindstrom

  • Affiliations:

  • Department of Biomedical Engineering, Vanderbilt University, Box 1804 Station B, Nashville, TN 37235, USA;Department of Electrical Engineering, Vanderbilt University, Box 1662 Station B, Nashville, TN 37235, USA;Department of Pediatrics, Neonatology Division, Vanderbilt University, A-0117 MCN, Nashville, TN 37232, USA

  • Venue:
  • Artificial Intelligence in Medicine
  • Year:
  • 1993

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Abstract

YAQ is an ontology for model-based reasoning in physiologic domains. YAQ is based on a hybrid algebra of qualitative and numerical values, and is designed to benefit from the rich and ever-changing nature of information available in a critical care monitoring environment. The focus of the project is on diagnosis of clinical conditions, prediction of the effects of therapy, and therapy management assistance. Two models of diagnosis are implemented in YAQ: diagnosis based on associations, and model-based diagnosis. The ontology is applied to the domain of ventilator management in infants with respiratory distress syndrome (RDS). The article describes the diagnostic capabilities of YAQ, illustrates these concepts on examples taken from actual patient records, and reports the results of an evaluation of the diagnostic performance on the RDS/assisted ventilation domain model.