Name
Abstract | ||
|---|---|---|
We present exploratory investigations of multimodal mining to help designing clinical guidelines for antibiotherapy. Our approach is based on the assumption that combining various sources of data, such as the literature, a clinical datawarehouse, as well as information regarding costs will result in better recommendations. Compared to our baseline recommendation system based on a question-answering engine built on top of PubMed, an improvement of +16% is observed when clinical data (i.e. resistance profiles) are injected into the model. In complement to PubMed, an alternative search strategy is reported, which is significantly improved by the use of the combined multimodal approach. These results suggest that combining literature-based discovery with structured data mining can significantly improve effectiveness of decision-support systems for authors of clinical practice guidelines. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.3233/978-1-60750-806-9-477 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
Multimodal mining,information retrieval,clinical guidelines,resistance profile,antibiotic cost | Data warehouse,Recommender system,Data mining,Clinical Practice,Multimodal therapy,Medicine,Data model | Conference |
Volume | ISSN | Citations |
169 | 0926-9630 | 0 |
PageRank | References | Authors |
0.34 | 6 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emilie Pasche | 1 | 99 | 15.93 |
| Julien Gobeill | 2 | 302 | 30.42 |
| Douglas Teodoro | 3 | 3 | 1.80 |
| Dina Vishnyakova | 4 | 113 | 11.16 |
| Arnaud Gaudinat | 5 | 62 | 12.47 |
| P Ruch | 6 | 650 | 38.72 |
| C Lovis | 7 | 85 | 19.90 |