Generation and Evaluation of Intraoperative Inferences for Automated Health Care Briefings on Patient Status After Bypass Surgery

McKeown, Kathleen; Jordan, Desmond; Concepcion, Kristian; Feiner, Steven; Hatzivassiloglou, Vasileios

The authors present a system that scans electronic records from cardiac surgery and uses inference rules to identify and classify abnormal events (e.g., hypertension) that may occur during critical surgical points (e.g., start of bypass). This vital information is used as the content of automatically generated briefings designed by MAGIC, a multimedia system that they are developing to brief intensive care unit clinicians on patient status after cardiac surgery. By recognizing patterns in the patient record, inferences concisely summarize detailed patient data.


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Also Published In

Journal of the American Medical Informatics Association

More About This Work

Academic Units
Computer Science
Published Here
April 8, 2013