Name
Title | ||
|---|---|---|
A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data. |
Abstract | ||
|---|---|---|
•A deep learning model, the stacked sparse auto-encoder based model, is proposed for cancer prediction.•The deep learning model, with pre-training and sparsity, outperforms classical models.•Important and abstract features are extracted.•Prediction results are presented on lung, stomach and breast cancer data. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cmpb.2018.10.004 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Stacked sparse auto-encoder,Cancer prediction,Gene expression data,Semi-supervised learning,Deep learning | Computer vision,Data set,Autoencoder,RNA-Seq,Computer science,Artificial intelligence,Deep learning,Cancer,Machine learning | Journal |
Volume | ISSN | Citations |
166 | 0169-2607 | 3 |
PageRank | References | Authors |
0.38 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yawen Xiao | 1 | 20 | 1.85 |
| Jun Wu | 2 | 22 | 3.69 |
| Zongli Lin | 3 | 3047 | 270.03 |
| Xiaodong Zhao | 4 | 32 | 5.40 |