Copyright
©The Author(s) 2024.
World J Clin Cases. Jun 26, 2024; 12(18): 3340-3350
Published online Jun 26, 2024. doi: 10.12998/wjcc.v12.i18.3340
Published online Jun 26, 2024. doi: 10.12998/wjcc.v12.i18.3340
Figure 2 Workflow of radiomics and deep transfer learning.
DTL: Deep transfer learning; FC: Fully connected layer; AP: Arterial phase; DP: Delayed phase; PVP: Portal venous phase; DLR: Deep learning radiomics; SVM: Support vector machines; MLP: Multilayer perceptron.
- Citation: Guan QL, Zhang HX, Gu JP, Cao GF, Ren WX. Omics-imaging signature-based nomogram to predict the progression-free survival of patients with hepatocellular carcinoma after transcatheter arterial chemoembolization. World J Clin Cases 2024; 12(18): 3340-3350
- URL: https://www.wjgnet.com/2307-8960/full/v12/i18/3340.htm
- DOI: https://dx.doi.org/10.12998/wjcc.v12.i18.3340