Name
Abstract | ||
|---|---|---|
Case-based approaches predict the behaviour of dynamic systems by analysing a given experimental setting in the context of others. To select similar cases and to control adaptation of cases, they employ general knowledge. If that is neither available nor inductively derivable, the knowledge implicit in cases can be utilized for a case-based ranking and adaptation of similar cases. We introduce the system GASES and its application to medical experimental studies to demonstrate this approach. (C) 1999 Elsevier Science B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1016/S0933-3657(98)00057-8 | ARTIFICIAL INTELLIGENCE IN MEDICINE |
Keywords | Field | DocType |
case-based reasoning, case-based similarity ranking, case-based adaptation, prediction, experimental studies | Data mining,Ranking,Computer science,Artificial intelligence,General knowledge,Case-based reasoning,Machine learning | Journal |
Volume | Issue | ISSN |
15 | 3 | 0933-3657 |
Citations | PageRank | References |
3 | 0.51 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Seitz | 1 | 22 | 4.63 |
| A M Uhrmacher | 2 | 3 | 0.51 |
| D Damm | 3 | 3 | 0.51 |