Automated modeling of medical decisions
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abstract: We have developed a graph grammar and a graph-grammar derivation system that, together, generate decision-theoretic models from unordered lists of medical terms. The medical terms represent considerations in a dilemma that confronts the patient and the health-care provider. Our current grammar ensures that several desirable structural properties are maintained in all derived decision models.
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| Abstract | We have developed a graph grammar and a gr … We have developed a graph grammar and a graph-grammar derivation system that, together, generate decision-theoretic models from unordered lists of medical terms. The medical terms represent considerations in a dilemma that confronts the patient and the health-care provider. Our current grammar ensures that several desirable structural properties are maintained in all derived decision models. maintained in all derived decision models. |
| Address | Washington D.C. + |
| Author | John W. Egar +, and Mark A. Musen + |
| Bibtype | techreport + |
| Institution | Knowledge Systems, AI Laboratory + |
| Key | KSL-93-30 + |
| Note | April Updated May 1993 Titlepage update August 1993. + |
| Number | KSL-93-30 + |
| Tag | Computer science + |
| Title | Automated Modeling of Medical Decisions + |
| Tr id | KSL-93-30 + |
| Year | 1993 + |
