Name
Title | ||
|---|---|---|
A deep learning based approach for classification of CerbB2 tumor cells in breast cancer. |
Abstract | ||
|---|---|---|
This study proposes a unique approach to classify CerbB2 tumor cell scores in breast cancer based on deep learning models. Another contribution of the study is the creation of a dataset from original breast cancer tissues. On the purpose of training, validating and testing with deep learning models cell fragments were generated from sample tissue images. CerbB2 tumor scores were generated for the cell fragments were classified with high performance by the aid of convolutional neural networks (CNN). |
Year | Venue | Keywords |
|---|---|---|
2017 | Signal Processing and Communications Applications Conference | CerbB2 marker,tumor,Convolutional Neural Networks (CNN),score,classification |
Field | DocType | ISSN |
Breast cancer,Convolutional neural network,Computer science,Artificial intelligence,Deep learning,Artificial neural network,Machine learning | Conference | 2165-0608 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gozde A. Tataroglu | 1 | 0 | 0.34 |
| Anil Genc | 2 | 8 | 1.47 |
| Kaan A. Kabakci | 3 | 0 | 0.34 |
| Abdulkerim Çapar | 4 | 19 | 4.28 |
| B. Ugur Töreyin | 5 | 146 | 12.43 |
| Hazim Kemal Ekenel | 6 | 377 | 44.16 |
| Ilknur Turkmen | 7 | 1 | 1.38 |
| Asli Cakir | 8 | 1 | 0.70 |