Name
Abstract | ||
|---|---|---|
In this paper, we formulate propagation patterns as the pairs of records in the same bacterial culture occurring within a fixed span in bacterial culture data. Then, we design the exhaustive search algorithm to extract all of the propagation patterns from bacterial culture data based on the extended principle of the 2-dimensional career map to determine whether two records in bacterial culture data belong to the same bacterial culture or the different ones. In particular, we focus on infectious propagation patterns, in which two patients are not identical, and they are in the same room and/or treated by the same physician. Finally, we give the experimental results to extract all of the propagation patterns and analyze them. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-50953-2_28 | Lecture Notes in Artificial Intelligence |
Field | DocType | Volume |
Data mining,Biology,Candida glabrata,Exhaustive search algorithm,Enterococcus faecium,Microbiological culture | Conference | 10091 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazuki Nagayama | 1 | 0 | 0.34 |
| Kouichi Hirata | 2 | 130 | 32.04 |
| Shigeki Yokoyama | 3 | 0 | 0.34 |
| Kimiko Matsuoka | 4 | 7 | 2.15 |