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Cited by in F6Publishing
For: Huang Y, Chen Y, Zhu H, Li W, Ge Y, Huang X, He J. A liver fibrosis staging method using cross-contrast network. Expert Systems with Applications 2019;130:124-31. [DOI: 10.1016/j.eswa.2019.03.049] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.3] [Reference Citation Analysis]
Number Citing Articles
1 Zeng X, Sun L. Research on Cross-Contrast Neural Network Based Intelligent Painting: Taking Oil Painting Language Classification as an Example. Computational Intelligence and Neuroscience 2022;2022:1-10. [DOI: 10.1155/2022/7827587] [Reference Citation Analysis]
2 Anteby R, Klang E, Horesh N, Nachmany I, Shimon O, Barash Y, Kopylov U, Soffer S. Deep learning for noninvasive liver fibrosis classification: A systematic review. Liver Int 2021;41:2269-78. [PMID: 34008300 DOI: 10.1111/liv.14966] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
3 Wang Y, Xu Z, Bai S, Wang Q, Chen Y, Li W, Huang X, Ge Y. Intelligent painting identification based on image perception in multimedia enterprise. Enterprise Information Systems. [DOI: 10.1080/17517575.2020.1755456] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
4 Li H, Liu X, Boumaraf S, Gong X, Liao D, Ma X. Deep Distance Map Regression Network with Shape-Aware Loss for Imbalanced Medical Image Segmentation. Machine Learning in Medical Imaging 2020. [DOI: 10.1007/978-3-030-59861-7_24] [Reference Citation Analysis]
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