| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4942224 | Artificial Intelligence in Medicine | 2017 | 41 Pages |
Abstract
We propose an innovative approach to the detection and analysis of interactions between CPGs considering different sources of temporal information (CPGs, ontological knowledge and execution logs), which is the first one in the literature that takes into account the temporal issues, and accounts for different application scenarios.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Luca Anselma, Luca Piovesan, Paolo Terenziani,