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For: Rasmusson A, Zilenaite D, Nestarenkaite A, Augulis R, Laurinaviciene A, Ostapenko V, Poskus T, Laurinavicius A. Immunogradient Indicators for Antitumor Response Assessment by Automated Tumor-Stroma Interface Zone Detection. Am J Pathol 2020;190:1309-22. [PMID: 32194048 DOI: 10.1016/j.ajpath.2020.01.018] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
Number Citing Articles
1 Yousif M, van Diest PJ, Laurinavicius A, Rimm D, van der Laak J, Madabhushi A, Schnitt S, Pantanowitz L. Artificial intelligence applied to breast pathology. Virchows Arch 2021. [PMID: 34791536 DOI: 10.1007/s00428-021-03213-3] [Reference Citation Analysis]
2 Budginaitė E, Morkūnas M, Laurinavičius A, Treigys P. Deep Learning Model for Cell Nuclei Segmentation and Lymphocyte Identification in Whole Slide Histology Images. Informatica. [DOI: 10.15388/20-infor442] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
3 Nestarenkaite A, Fadhil W, Rasmusson A, Susanti S, Hadjimichael E, Laurinaviciene A, Ilyas M, Laurinavicius A. Immuno-Interface Score to Predict Outcome in Colorectal Cancer Independent of Microsatellite Instability Status. Cancers (Basel) 2020;12:E2902. [PMID: 33050344 DOI: 10.3390/cancers12102902] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
4 Mungenast F, Fernando A, Nica R, Boghiu B, Lungu B, Batra J, Ecker RC. Next-Generation Digital Histopathology of the Tumor Microenvironment. Genes (Basel) 2021;12:538. [PMID: 33917241 DOI: 10.3390/genes12040538] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
5 Fu T, Dai LJ, Wu SY, Xiao Y, Ma D, Jiang YZ, Shao ZM. Spatial architecture of the immune microenvironment orchestrates tumor immunity and therapeutic response. J Hematol Oncol 2021;14:98. [PMID: 34172088 DOI: 10.1186/s13045-021-01103-4] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
6 Laurinavicius A, Rasmusson A, Plancoulaine B, Shribak M, Levenson R. Machine-Learning-Based Evaluation of Intratumoral Heterogeneity and Tumor-Stroma Interface for Clinical Guidance. Am J Pathol 2021:S0002-9440(21)00165-6. [PMID: 33895120 DOI: 10.1016/j.ajpath.2021.04.008] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Radziuviene G, Rasmusson A, Augulis R, Grineviciute RB, Zilenaite D, Laurinaviciene A, Ostapenko V, Laurinavicius A. Intratumoral Heterogeneity and Immune Response Indicators to Predict Overall Survival in a Retrospective Study of HER2-Borderline (IHC 2+) Breast Cancer Patients. Front Oncol 2021;11:774088. [PMID: 34858854 DOI: 10.3389/fonc.2021.774088] [Reference Citation Analysis]
8 Wang YQ, Liu X, Xu C, Jiang W, Xu SY, Zhang Y, Liang YL, Li JY, Li Q, Chen YP, Zhao Y, Yun JP, Liu N, Li YQ, Ma J. Spatial heterogeneity of immune infiltration predicts the prognosis of nasopharyngeal carcinoma patients. Oncoimmunology 2021;10:1976439. [PMID: 34721946 DOI: 10.1080/2162402X.2021.1976439] [Reference Citation Analysis]