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For: Cheng J, Han Z, Mehra R, Shao W, Cheng M, Feng Q, Ni D, Huang K, Cheng L, Zhang J. Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma. Nat Commun 2020;11:1778. [PMID: 32286325 DOI: 10.1038/s41467-020-15671-5] [Cited by in Crossref: 23] [Cited by in F6Publishing: 25] [Article Influence: 11.5] [Reference Citation Analysis]
Number Citing Articles
1 Patel AU, Mohanty SK, Parwani AV. Applications of Digital and Computational Pathology and Artificial Intelligence in Genitourinary Pathology Diagnostics. Surgical Pathology Clinics 2022;15:759-785. [DOI: 10.1016/j.path.2022.08.001] [Reference Citation Analysis]
2 Alsaleh L, Li C, Couetil JL, Ye Z, Huang K, Zhang J, Chen C, Johnson TS. Spatial Transcriptomic Analysis Reveals Associations between Genes and Cellular Topology in Breast and Prostate Cancers. Cancers 2022;14:4856. [DOI: 10.3390/cancers14194856] [Reference Citation Analysis]
3 Ning S, Pan Y, Ji Y, Huang R, Yang H, Huang Q. Imaging genetic association analysis of triple-negative breast cancer based on the integration of prior sample information.. [DOI: 10.21203/rs.3.rs-1959328/v1] [Reference Citation Analysis]
4 Patel AU, Shaker N, Mohanty S, Sharma S, Gangal S, Eloy C, Parwani AV. Cultivating Clinical Clarity through Computer Vision: A Current Perspective on Whole Slide Imaging and Artificial Intelligence. Diagnostics 2022;12:1778. [DOI: 10.3390/diagnostics12081778] [Reference Citation Analysis]
5 Zhu J, Wu W, Zhang Y, Lin S, Jiang Y, Liu R, Zhang H, Wang X. Computational Analysis of Pathological Image Enables Interpretable Prediction for Microsatellite Instability. Front Oncol 2022;12:825353. [DOI: 10.3389/fonc.2022.825353] [Reference Citation Analysis]
6 Liang J, Yang X, Huang Y, Li H, He S, Hu X, Chen Z, Xue W, Cheng J, Ni D. Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis. Medical Image Analysis 2022;79:102461. [DOI: 10.1016/j.media.2022.102461] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
7 Song Q, Yu H, Han J, Qiang Lv JL, Yang H. Exosomes in urological diseases - Biological functions and clinical applications. Cancer Lett 2022;:215809. [PMID: 35777716 DOI: 10.1016/j.canlet.2022.215809] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Ren F, Wang D, Zhang X, Zhao N, Wang X, Zhang Y, Li L. Cross Analysis of Genomic-Pathologic Features on Multiple Primary Hepatocellular Carcinoma. Front Genet 2022;13:846517. [DOI: 10.3389/fgene.2022.846517] [Reference Citation Analysis]
9 Rasmussen R, Sanford T, Parwani AV, Pedrosa I. Artificial Intelligence in Kidney Cancer. Am Soc Clin Oncol Educ Book 2022;42:1-11. [PMID: 35580292 DOI: 10.1200/EDBK_350862] [Reference Citation Analysis]
10 Wu Y, Cheng M, Huang S, Pei Z, Zuo Y, Liu J, Yang K, Zhu Q, Zhang J, Hong H, Zhang D, Huang K, Cheng L, Shao W. Recent Advances of Deep Learning for Computational Histopathology: Principles and Applications. Cancers 2022;14:1199. [DOI: 10.3390/cancers14051199] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]
11 Liu X, Xu A, Huang J, Shen H, Liu Y. Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment. J Int Med Res 2022;50:3000605211067688. [PMID: 34986677 DOI: 10.1177/03000605211067688] [Reference Citation Analysis]
12 Wang D, Li J, Sun Y, Ding X, Zhang X, Liu S, Han B, Wang H, Duan X, Sun T. A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients. Front Public Health 2021;9:754348. [PMID: 34722452 DOI: 10.3389/fpubh.2021.754348] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 4.0] [Reference Citation Analysis]
13 Deng J, Zeng W, Luo S, Kong W, Shi Y, Li Y, Zhang H. Integrating multiple genomic imaging data for the study of lung metastasis in sarcomas using multi-dimensional constrained joint non-negative matrix factorization. Information Sciences 2021;576:24-36. [DOI: 10.1016/j.ins.2021.06.058] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 5.0] [Reference Citation Analysis]
14 Chao S, Belanger D. Generalizing Few-Shot Classification of Whole-Genome Doubling Across Cancer Types. 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 2021. [DOI: 10.1109/iccvw54120.2021.00377] [Reference Citation Analysis]
15 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] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
16 Lee M, Wei S, Anaokar J, Uzzo R, Kutikov A. Kidney cancer management 3.0: can artificial intelligence make us better? Curr Opin Urol 2021;31:409-15. [PMID: 33882560 DOI: 10.1097/MOU.0000000000000881] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
17 Cheng J, Liu Y, Huang W, Hong W, Wang L, Ni D. Identifying novel prognostic markers and genotype-phenotype associations in endometrioid endometrial carcinoma by computational analysis of histopathological images. Medicine in Omics 2021;1:100005. [DOI: 10.1016/j.meomic.2021.100005] [Reference Citation Analysis]
18 Fang R, Wang X, Xia Q, Zhao M, Zhang H, Wang X, Ye S, Cheng K, Liang Y, Cheng Y, Gu Y, Rao Q. Nuclear translocation of ASPL-TFE3 fusion protein creates favorable metabolism by mediating autophagy in translocation renal cell carcinoma. Oncogene 2021;40:3303-17. [PMID: 33846569 DOI: 10.1038/s41388-021-01776-8] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
19 Cheng J, Liu Y, Huang W, Hong W, Wang L, Zhan X, Han Z, Ni D, Huang K, Zhang J. Computational Image Analysis Identifies Histopathological Image Features Associated With Somatic Mutations and Patient Survival in Gastric Adenocarcinoma. Front Oncol 2021;11:623382. [PMID: 33869007 DOI: 10.3389/fonc.2021.623382] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
20 Jiao Y, Li J, Qian C, Fei S. Deep learning-based tumor microenvironment analysis in colon adenocarcinoma histopathological whole-slide images. Comput Methods Programs Biomed 2021;204:106047. [PMID: 33789213 DOI: 10.1016/j.cmpb.2021.106047] [Cited by in Crossref: 11] [Cited by in F6Publishing: 9] [Article Influence: 11.0] [Reference Citation Analysis]
21 Sprint G, Cook DJ, Fritz R. Behavioral Differences Between Subject Groups Identified Using Smart Homes and Change Point Detection. IEEE J Biomed Health Inform 2021;25:559-67. [PMID: 32750924 DOI: 10.1109/JBHI.2020.2999607] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 7.0] [Reference Citation Analysis]
22 Xiao R, Debreuve E, Ambrosetti D, Descombes X. Renal Cell Carcinoma Classification from Vascular Morphology. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 2021. [DOI: 10.1007/978-3-030-87231-1_59] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
23 Galan EA, Zhao H, Wang X, Dai Q, Huck WT, Ma S. Intelligent Microfluidics: The Convergence of Machine Learning and Microfluidics in Materials Science and Biomedicine. Matter 2020;3:1893-922. [DOI: 10.1016/j.matt.2020.08.034] [Cited by in Crossref: 29] [Cited by in F6Publishing: 32] [Article Influence: 14.5] [Reference Citation Analysis]