| Generating diagnositc rules directly from experimental data | |
|---|---|
| 學年 | 86 |
| 學期 | 1 |
| 出版（發表）日期 | 1997-12-01 |
| 作品名稱 | Generating diagnositc rules directly from experimental data |
| 作品名稱（其他語言） | |
| 著者 | Su, Mu-chun;Hsieh, Ching-tang;Chin, Chieh-ching |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | Singapore: World Scientific Publishing Co. Pte. Ltd. |
| 著錄名稱、卷期、頁數 | Biomedical Engineering: Applications, Basis and Communications 9(6), pp.9-14 |
| 摘要 | Traditionally, a major task in building a medical diagnosis expert system is the process of acquiring the required knowledge in the form of production rules. alternative knowledge acquisition approaches to articulating knowledge required for diagnostic tasks are presented in this paper. Each approach has its own advantages and disadvantages. The ultimate goal of these approaches is to free human experts from tedious diagnosis loads. The effectiveness of these approaches is demonstrated by an example of a hypothesis regarding the pathophysiology of diabetes. |
| 關鍵字 | Neural networks;Fuzzy systems;Computer-aided expert systems;Medical diagnosis |
| 語言 | en |
| ISSN | 1016-2372 |
| 期刊性質 | 國外 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | |
| 國別 | SGP |
| 公開徵稿 | |
| 出版型式 | 紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/60738 ) |
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