Name
Title | ||
|---|---|---|
Application Of Inductive Bayesian Hierarchical Clustering Algorithm To Identify Brain Tumors |
Abstract | ||
|---|---|---|
The article presents the results of research concerning development of inductive algorithm for hierarchical Bayesian clustering of gene expression of patients with two types of brain tumors and healthy individuals. The study carried out comparative studies of the clustering quality of inductive and classical methods of Bayesian hierarchical clustering algorithm (BHC). It is proposed to apply the moving average and FFT filtering methods for data dimension reducing. The basic principles of creating an inductive model of objective clustering are formed, the results of clustering are shown at various levels of data dimension reducing, the advantages of objective clustering BHC in comparison with the canonical BHC algorithm are determined. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/978-3-030-54215-3_36 | LECTURE NOTES IN COMPUTATIONAL INTELLIGENCE AND DECISION MAKING (ISDMCI 2020) |
Keywords | DocType | Volume |
Glioblastoma, Brain tumor, Oligodendroglial tumors, Glioblastoma multiforme profiling of gene expression, Inductive modeling, Bayesian hierarchical algorithm, External balance criterion, Data dimension reducing, Normalizing, Exploratory analysis criterion, Gene expression profiles | Conference | 1246 |
ISSN | Citations | PageRank |
2194-5357 | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iryna Lurie | 1 | 1 | 1.71 |
| Volodymyr Lytvynenko | 2 | 4 | 2.54 |
| Serge Olszewski | 3 | 0 | 0.34 |
| Mariia Voronenko | 4 | 1 | 2.04 |
| Waldemar Woicik | 5 | 0 | 0.34 |
| Oleg Boskin | 6 | 1 | 1.03 |
| Ulzhalgas Zhunissova | 7 | 0 | 0.68 |
| Michael Sherstiuk | 8 | 0 | 0.34 |