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Cited by in F6Publishing
For: Gupta R, Kurc T, Sharma A, Almeida JS, Saltz J. The Emergence of Pathomics. Curr Pathobiol Rep 2019;7:73-84. [DOI: 10.1007/s40139-019-00200-x] [Cited by in Crossref: 13] [Cited by in F6Publishing: 5] [Article Influence: 4.3] [Reference Citation Analysis]
Number Citing Articles
1 Brancato V, Garbino N, Salvatore M, Cavaliere C. MRI-Based Radiomic Features Help Identify Lesions and Predict Histopathological Grade of Hepatocellular Carcinoma. Diagnostics 2022;12:1085. [DOI: 10.3390/diagnostics12051085] [Reference Citation Analysis]
2 Wan L, Sun Z, Peng W, Wang S, Li J, Zhao Q, Wang S, Ouyang H, Zhao X, Zou S, Zhang H. Selecting Candidates for Organ-Preserving Strategies After Neoadjuvant Chemoradiotherapy for Rectal Cancer: Development and Validation of a Model Integrating MRI Radiomics and Pathomics. J Magn Reson Imaging 2022. [PMID: 35142001 DOI: 10.1002/jmri.28108] [Reference Citation Analysis]
3 Gupta R, Le H, Van Arnam J, Belinsky D, Hasan M, Samaras D, Kurc T, Saltz JH. Characterizing Immune Responses in Whole Slide Images of Cancer With Digital Pathology and Pathomics. Curr Pathobiol Rep 2020;8:133-48. [DOI: 10.1007/s40139-020-00217-7] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
4 Valous NA, Moraleda RR, Jäger D, Zörnig I, Halama N. Interrogating the microenvironmental landscape of tumors with computational image analysis approaches. Semin Immunol 2020;48:101411. [PMID: 33168423 DOI: 10.1016/j.smim.2020.101411] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
5 Arjmand B, Hamidpour SK, Tayanloo-beik A, Goodarzi P, Aghayan HR, Adibi H, Larijani B. Machine Learning: A New Prospect in Multi-Omics Data Analysis of Cancer. Front Genet 2022;13:824451. [DOI: 10.3389/fgene.2022.824451] [Reference Citation Analysis]
6 Schuettfort VM, Pradere B, Rink M, Comperat E, Shariat SF. Pathomics in urology. Curr Opin Urol 2020;30:823-31. [PMID: 32881725 DOI: 10.1097/MOU.0000000000000813] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 6.0] [Reference Citation Analysis]
7 Chen P, El Hussein S, Xing F, Aminu M, Kannapiran A, Hazle JD, Medeiros LJ, Wistuba II, Jaffray D, Khoury JD, Wu J. Chronic Lymphocytic Leukemia Progression Diagnosis with Intrinsic Cellular Patterns via Unsupervised Clustering. Cancers 2022;14:2398. [DOI: 10.3390/cancers14102398] [Reference Citation Analysis]
8 Porcu M, Solinas C, Mannelli L, Micheletti G, Lambertini M, Willard-Gallo K, Neri E, Flanders AE, Saba L. Radiomics and "radi-…omics" in cancer immunotherapy: a guide for clinicians. Crit Rev Oncol Hematol 2020;154:103068. [PMID: 32805498 DOI: 10.1016/j.critrevonc.2020.103068] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Classe M, Lerousseau M, Scoazec JY, Deutsch E. Perspectives in pathomics in head and neck cancer. Curr Opin Oncol 2021;33:175-83. [PMID: 33782358 DOI: 10.1097/CCO.0000000000000731] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
10 Becker JU, Mayerich D, Padmanabhan M, Barratt J, Ernst A, Boor P, Cicalese PA, Mohan C, Nguyen HV, Roysam B. Artificial intelligence and machine learning in nephropathology. Kidney Int 2020;98:65-75. [PMID: 32475607 DOI: 10.1016/j.kint.2020.02.027] [Cited by in Crossref: 17] [Cited by in F6Publishing: 12] [Article Influence: 8.5] [Reference Citation Analysis]