Name
Abstract | ||
|---|---|---|
Knowledge acquisition is known to be a critical bottleneck in building expert systems. In past decades, various methods and systems have been proposed to efficiently elicit expertise from domain experts. However, in building a medical expert system, disease symptoms are usually treated as time-irrelevant attributes, such that much important information is abandoned and hence, the performance of the constructed expert systems is significantly affected. To cope with this problem, in this paper, we propose a time scale-oriented approach to eliciting medical knowledge from domain experts. The novel approach takes the time scale into consideration, such that the variant of disease symptoms in different time scales can be precisely expressed. An application to the development of a medical expert system has depicted the superiority of our approach. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.eswa.2005.09.050 | Expert Systems with Applications |
Keywords | DocType | Volume |
Medical expert systems,Knowledge acquisition,Artificial intelligence,Expert systems | Journal | 31 |
Issue | ISSN | Citations |
2 | 0957-4174 | 1 |
PageRank | References | Authors |
0.42 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gwo-Haur Hwang | 1 | 89 | 10.81 |
| Jun-ming Chen | 2 | 40 | 5.68 |
| Gwo-Jen Hwang | 3 | 3399 | 217.05 |
| Hui-chun Chu | 4 | 673 | 42.23 |