Name
Abstract | ||
|---|---|---|
There are a number of obstacles to successful operationalization of clinical practice guidelines, including the difficulty in accurately representing a statement's decidability or an action's executability. Both require reasoning with incomplete and imprecise information, and we present one means of processing such information. We begin with a brief overview of fuzzy set theory, in which elements can have partial memberships in multiple sets. With fuzzy inferencing, these sets can be combined to create multiple conclusions, each with varying degrees of truth. We demonstrate a fuzzy model developed from a published clinical practice guideline on the management of first simple febrile seizures. Although the creation of fuzzy sets can be an arbitrary process, we believe that fuzzy inferencing is an effective tool for the expression of guideline recommendations, and that it can be useful for the management of imprecision and uncertainty. |
Year | Venue | Keywords |
|---|---|---|
1997 | JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION | fuzzy logic |
Field | DocType | Issue |
Fuzzy model,Computer science,Clinical Practice,Fuzzy logic,Fuzzy set,Simple febrile seizure,Decidability,Artificial intelligence,Operationalization,Guideline | Conference | SUPnan |
ISSN | Citations | PageRank |
1067-5027 | 13 | 3.93 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| James C. S. Liu | 1 | 13 | 3.93 |
| Richard N. Shiffman | 2 | 124 | 26.09 |