The use of misclassification costs to learn rule-based decision support models for cost-effective hospital admission strategies

Ambrosino R, Buchanan BG, Cooper GF, Fine MJ. The use of misclassification costs to learn rule-based decision support models for cost-effective hospital admission strategies. In: Proceedings of the Symposium on Computer Applications in Medical Care (1995) 304–308.  PMID:  8563290

Cost-effective health care is at the forefront oftoday's important health-related issues. A research teamii at the University ofPittsburgh has been interested in lowering the cost ofmedical care by attempting to define a subset of patients with comnmtnunity-acquired pneumionia for whoin outpatient therapy is appropriate and safe. Sensitivity and specificity requirementsfor this domain make it difficult to use rule-based learning algorithmtis with standard mteasures of performtance based on accuracy. This paper describes the use of misclassification costs to assist a rule-based machinelearningprogramii in deriving a decision-support aidfor choosing outpatient therapy for patients wsith community-acquiredpneumnonia.

Publication Year: 
1995
Faculty Author: 
Publication Credits: 
Ambrosino R, Buchanan BG, Cooper GF, Fine MJ.
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