Name
Abstract | ||
|---|---|---|
We propose a hierarchical clustering method for prognostic clustering of cancer patients. Dissimilarity between two subsets of patients is defined as the area between two corresponding Kaplan-Meier curves. The proposed method is applied to the breast cancer data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute and compared with the linkage approach. The proposed method is convenient to use and can generate dendrograms compatible with those from the linkage approach. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CHASE.2016.35 | 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) |
Keywords | Field | DocType |
TNM,survival,breast cancer,hierarchical clustering,area between curves,dendrogram,prognostic system | Hierarchical clustering,Data mining,Breast cancer,Dendrogram,Survival analysis,Cluster analysis,Medicine,Cancer | Conference |
ISBN | Citations | PageRank |
978-1-5090-0944-2 | 0 | 0.34 |
References | Authors | |
2 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dechang Chen | 1 | 402 | 33.51 |
| Huan Wang | 2 | 53 | 21.74 |
| Donald E Henson | 3 | 7 | 1.42 |
| Li Sheng | 4 | 70 | 8.34 |
| Matthew T. Hueman | 5 | 0 | 0.34 |
| Arnold M. Schwartz | 6 | 14 | 2.43 |