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Cited by in F6Publishing
For: Failmezger H, Muralidhar S, Rullan A, de Andrea CE, Sahai E, Yuan Y. Topological Tumor Graphs: A Graph-Based Spatial Model to Infer Stromal Recruitment for Immunosuppression in Melanoma Histology. Cancer Res 2020;80:1199-209. [PMID: 31874858 DOI: 10.1158/0008-5472.CAN-19-2268] [Cited by in Crossref: 9] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Mi H, Bivalacqua TJ, Kates M, Seiler R, Black PC, Popel AS, Baras AS. Predictive models of response to neoadjuvant chemotherapy in muscle-invasive bladder cancer using nuclear morphology and tissue architecture. Cell Rep Med 2021;2:100382. [PMID: 34622225 DOI: 10.1016/j.xcrm.2021.100382] [Reference Citation Analysis]
2 Lee K, Lockhart JH, Xie M, Chaudhary R, Slebos RJC, Flores ER, Chung CH, Tan AC. Deep Learning of Histopathology Images at the Single Cell Level. Front Artif Intell 2021;4:754641. [PMID: 34568816 DOI: 10.3389/frai.2021.754641] [Reference Citation Analysis]
3 Xu Z, Li Y, Wang Y, Zhang S, Huang Y, Yao S, Han C, Pan X, Shi Z, Mao Y, Xu Y, Huang X, Lin H, Chen X, Liang C, Li Z, Zhao K, Zhang Q, Liu Z. A deep learning quantified stroma-immune score to predict survival of patients with stage II-III colorectal cancer. Cancer Cell Int 2021;21:585. [PMID: 34717647 DOI: 10.1186/s12935-021-02297-w] [Reference Citation Analysis]
4 Peng Y, Chu Y, Chen Z, Zhou W, Wan S, Xiao Y, Zhang Y, Li J. Combining texture features of whole slide images improves prognostic prediction of recurrence-free survival for cutaneous melanoma patients. World J Surg Oncol 2020;18:130. [PMID: 32546168 DOI: 10.1186/s12957-020-01909-5] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]