Name
Abstract | ||
|---|---|---|
This paper highlights the shortcomings of current systems of nosocomial infection control and shows how techniques borrowed from statistics and Artificial Intelligence, in particular clustering, can be used effectively to enhance these systems beyond confirmation and into the more important realms of detection and prediction. A tool called HIC and examined in collaboration with the Cardiff Public Health Laboratory is presented. Preliminary experiments with the system demonstrate promise. In particular, the system was able to uncover a previously undiscovered cross-infection incident. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1007/3-540-48229-6_4 | AIME '87 |
Keywords | Field | DocType |
important realm,cardiff public health laboratory,undiscovered cross-infection incident,nosocomial infection control,artificial intelligence,particular clustering,current system,preliminary experiment,incremental clustering,infectious outbreaks,artificial intelligent,public health | Relational database,Computer science,Outbreak,Artificial intelligence,Cluster analysis,Machine learning,Nosocomial infection control | Conference |
Volume | ISSN | ISBN |
2101 | 0302-9743 | 3-540-42294-3 |
Citations | PageRank | References |
5 | 0.49 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Timothy Langford | 1 | 5 | 0.49 |
| Christophe G. Giraud-carrier | 2 | 680 | 59.41 |
| John Magee | 3 | 5 | 1.16 |