Name
Abstract | ||
|---|---|---|
This paper proposes a method for construction of a clinical pathway based on dual clustering which consists of attribute and sampling clustering. The method consists of the following four steps: first, couting numbers of nursing orders of a given disease are extracted from hospital information system. Second, orders are classified into several groups by using clustering (sample clustering). Third, attributes clustering is applied to the data. Finally, original temporal data are split into several sub-tables by uisn the results of attribute clustering and the first step will be repeated in a recursive way. After the grouping results are stable, a new pathway will be constructed from all the induced results. The method was applied to a dataset of a disease extracted from a hospital information system. The results show that the proposed method constructed a clinical pathway, which was not only similar to the pathway manually acquired from medical experts but also discovered nursing orders which they forget to include. Clustering |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2818869.2818932 | Proceedings of the ASE BigData & SocialInformatics 2015 |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shusaku Tsumoto | 1 | 1820 | 294.19 |
| Shoji Hirano | 2 | 560 | 99.17 |
| Haruko Iwata | 3 | 27 | 12.48 |