Name
Abstract | ||
|---|---|---|
•Mining complex texture features is critical for accurate liver fibrosis staging.•It is the first experimental study combines IBS with convolutional network.•Computational results suggest the network performs well on average. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2019.03.049 | Expert Systems with Applications |
Keywords | Field | DocType |
Convolutional neural network,IBS theory,Liver fibrosis,Cross-contrast | Data mining,Binary classification,Computer science,Convolutional neural network,Artificial neural network,Statistical analysis | Journal |
Volume | ISSN | Citations |
130 | 0957-4174 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yudan Huang | 1 | 0 | 0.34 |
| Ying Chen | 2 | 3 | 1.27 |
| Haochuan Zhu | 3 | 0 | 0.34 |
| Weifeng Li | 4 | 0 | 1.01 |
| Yun Ge | 5 | 0 | 1.01 |
| Xiaolin Huang | 6 | 0 | 1.01 |
| Jian He | 7 | 0 | 0.34 |