Abstract
Cost-effective health care is at the forefront of today's important health-related issues. A research team at the University of Pittsburgh has been interested in lowering the cost of medical care by attempting to define a subset of patients with community-acquire pneumonia for whom outpatient therapy is appropriate and safe. Sensitivity and specificity requirements for this domain make it difficult to use rule-based learning algorithms with standard measures of performance based on accuracy. This paper describes the use of misclassification costs to assist a rule-based machine-learning program in deriving a decision-support aid for choosing outpatient therapy for patients with community-acquired pneumonia.
Full text
PDF
Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- McNeil B. J., Keller E., Adelstein S. J. Primer on certain elements of medical decision making. N Engl J Med. 1975 Jul 31;293(5):211–215. doi: 10.1056/NEJM197507312930501. [DOI] [PubMed] [Google Scholar]