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For: Echle A, Rindtorff NT, Brinker TJ, Luedde T, Pearson AT, Kather JN. Deep learning in cancer pathology: a new generation of clinical biomarkers. Br J Cancer 2021;124:686-96. [PMID: 33204028 DOI: 10.1038/s41416-020-01122-x] [Cited by in Crossref: 20] [Cited by in F6Publishing: 19] [Article Influence: 10.0] [Reference Citation Analysis]
Number Citing Articles
1 Liang F, Wang S, Zhang K, Liu TJ, Li JN. Development of artificial intelligence technology in diagnosis, treatment, and prognosis of colorectal cancer. World J Gastrointest Oncol 2022; 14(1): 124-152 [DOI: 10.4251/wjgo.v14.i1.124] [Reference Citation Analysis]
2 Wharton KA Jr, Wood D, Manesse M, Maclean KH, Leiss F, Zuraw A. Tissue Multiplex Analyte Detection in Anatomic Pathology - Pathways to Clinical Implementation. Front Mol Biosci 2021;8:672531. [PMID: 34386519 DOI: 10.3389/fmolb.2021.672531] [Reference Citation Analysis]
3 Sadhwani A, Chang HW, Behrooz A, Brown T, Auvigne-Flament I, Patel H, Findlater R, Velez V, Tan F, Tekiela K, Wulczyn E, Yi ES, Mermel CH, Hanks D, Chen PC, Kulig K, Batenchuk C, Steiner DF, Cimermancic P. Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images. Sci Rep 2021;11:16605. [PMID: 34400666 DOI: 10.1038/s41598-021-95747-4] [Reference Citation Analysis]
4 Huang X, Huang K, Johnson T, Radovich M, Zhang J, Ma J, Wang Y. ParsVNN: parsimony visible neural networks for uncovering cancer-specific and drug-sensitive genes and pathways. NAR Genom Bioinform 2021;3:lqab097. [PMID: 34729476 DOI: 10.1093/nargab/lqab097] [Reference Citation Analysis]
5 Holgate ST. Accelerating the transition of clinical science to translational medicine. Clin Sci (Lond) 2021;135:2423-8. [PMID: 34709405 DOI: 10.1042/CS20210846] [Reference Citation Analysis]
6 Karube K, Kakimoto Y, Tonozuka Y, Ohshima K. The expression of CD30 and its clinico-pathologic significance in peripheral T-cell lymphomas. Expert Rev Hematol 2021;:1-11. [PMID: 34263699 DOI: 10.1080/17474086.2021.1955344] [Reference Citation Analysis]
7 Howard FM, Dolezal J, Kochanny S, Schulte J, Chen H, Heij L, Huo D, Nanda R, Olopade OI, Kather JN, Cipriani N, Grossman RL, Pearson AT. The impact of site-specific digital histology signatures on deep learning model accuracy and bias. Nat Commun 2021;12:4423. [PMID: 34285218 DOI: 10.1038/s41467-021-24698-1] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
8 Bussola N, Papa B, Melaiu O, Castellano A, Fruci D, Jurman G. Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology. Int J Mol Sci 2021;22:8804. [PMID: 34445517 DOI: 10.3390/ijms22168804] [Reference Citation Analysis]
9 Kiehl L, Kuntz S, Höhn J, Jutzi T, Krieghoff-Henning E, Kather JN, Holland-Letz T, Kopp-Schneider A, Chang-Claude J, Brobeil A, von Kalle C, Fröhling S, Alwers E, Brenner H, Hoffmeister M, Brinker TJ. Deep learning can predict lymph node status directly from histology in colorectal cancer. Eur J Cancer 2021;157:464-73. [PMID: 34649117 DOI: 10.1016/j.ejca.2021.08.039] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Janssen BV, Theijse R, van Roessel S, de Ruiter R, Berkel A, Huiskens J, Busch OR, Wilmink JW, Kazemier G, Valkema P, Farina A, Verheij J, de Boer OJ, Besselink MG. Artificial Intelligence-Based Segmentation of Residual Tumor in Histopathology of Pancreatic Cancer after Neoadjuvant Treatment. Cancers (Basel) 2021;13:5089. [PMID: 34680241 DOI: 10.3390/cancers13205089] [Reference Citation Analysis]
11 Kourou K, Exarchos KP, Papaloukas C, Sakaloglou P, Exarchos T, Fotiadis DI. Applied machine learning in cancer research: A systematic review for patient diagnosis, classification and prognosis. Comput Struct Biotechnol J 2021;19:5546-55. [PMID: 34712399 DOI: 10.1016/j.csbj.2021.10.006] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Le'Clerc Arrastia J, Heilenkötter N, Otero Baguer D, Hauberg-Lotte L, Boskamp T, Hetzer S, Duschner N, Schaller J, Maass P. Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma. J Imaging 2021;7:71. [PMID: 34460521 DOI: 10.3390/jimaging7040071] [Reference Citation Analysis]
13 Schüffler PJ, Geneslaw L, Yarlagadda DVK, Hanna MG, Samboy J, Stamelos E, Vanderbilt C, Philip J, Jean MH, Corsale L, Manzo A, Paramasivam NHG, Ziegler JS, Gao J, Perin JC, Kim YS, Bhanot UK, Roehrl MHA, Ardon O, Chiang S, Giri DD, Sigel CS, Tan LK, Murray M, Virgo C, England C, Yagi Y, Sirintrapun SJ, Klimstra D, Hameed M, Reuter VE, Fuchs TJ. Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center. J Am Med Inform Assoc 2021;28:1874-84. [PMID: 34260720 DOI: 10.1093/jamia/ocab085] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
14 Xie X, Wang X, Liang Y, Yang J, Wu Y, Li L, Sun X, Bing P, He B, Tian G, Shi X. Evaluating Cancer-Related Biomarkers Based on Pathological Images: A Systematic Review. Front Oncol 2021;11:763527. [PMID: 34900711 DOI: 10.3389/fonc.2021.763527] [Reference Citation Analysis]
15 Muti HS, Heij LR, Keller G, Kohlruss M, Langer R, Dislich B, Cheong JH, Kim YW, Kim H, Kook MC, Cunningham D, Allum WH, Langley RE, Nankivell MG, Quirke P, Hayden JD, West NP, Irvine AJ, Yoshikawa T, Oshima T, Huss R, Grosser B, Roviello F, d'Ignazio A, Quaas A, Alakus H, Tan X, Pearson AT, Luedde T, Ebert MP, Jäger D, Trautwein C, Gaisa NT, Grabsch HI, Kather JN. Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study. Lancet Digit Health 2021;3:e654-64. [PMID: 34417147 DOI: 10.1016/S2589-7500(21)00133-3] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
16 Kuntz S, Krieghoff-Henning E, Kather JN, Jutzi T, Höhn J, Kiehl L, Hekler A, Alwers E, von Kalle C, Fröhling S, Utikal JS, Brenner H, Hoffmeister M, Brinker TJ. Gastrointestinal cancer classification and prognostication from histology using deep learning: Systematic review. Eur J Cancer 2021;155:200-15. [PMID: 34391053 DOI: 10.1016/j.ejca.2021.07.012] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
17 Schrammen PL, Ghaffari Laleh N, Echle A, Truhn D, Schulz V, Brinker TJ, Brenner H, Chang-Claude J, Alwers E, Brobeil A, Kloor M, Heij LR, Jäger D, Trautwein C, Grabsch HI, Quirke P, West NP, Hoffmeister M, Kather JN. Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology. J Pathol 2021. [PMID: 34561876 DOI: 10.1002/path.5800] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
18 Fitzgerald J, Higgins D, Mazo Vargas C, Watson W, Mooney C, Rahman A, Aspell N, Connolly A, Aura Gonzalez C, Gallagher W. Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer. J Clin Pathol 2021;74:429-34. [PMID: 34117103 DOI: 10.1136/jclinpath-2020-207351] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
19 Jang HJ, Lee A, Kang J, Song IH, Lee SH. Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach. World J Gastroenterol 2021; 27(44): 7687-7704 [PMID: 34908807 DOI: 10.3748/wjg.v27.i44.7687] [Reference Citation Analysis]
20 Veta M, van Diest PJ, Vink A. Can automatic image analysis replace the pathologist in cardiac allograft rejection diagnosis? Eur Heart J 2021;42:2370-2. [PMID: 34000014 DOI: 10.1093/eurheartj/ehab226] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
21 Loeffler CML, Ortiz Bruechle N, Jung M, Seillier L, Rose M, Laleh NG, Knuechel R, Brinker TJ, Trautwein C, Gaisa NT, Kather JN. Artificial Intelligence-based Detection of FGFR3 Mutational Status Directly from Routine Histology in Bladder Cancer: A Possible Preselection for Molecular Testing? Eur Urol Focus 2021:S2405-4569(21)00113-9. [PMID: 33895087 DOI: 10.1016/j.euf.2021.04.007] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
22 Chen ZH, Lin L, Wu CF, Li CF, Xu RH, Sun Y. Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine. Cancer Commun (Lond) 2021;41:1100-15. [PMID: 34613667 DOI: 10.1002/cac2.12215] [Reference Citation Analysis]
23 Beharry A, Gong Y, Kim JC, Hanlon KS, Nammour J, Hieber K, Eichler F, Cheng M, Stemmer-Rachamimov A, Stankovic KM, Welling DB, Ng C, Maguire CA. The AAV9 Variant Capsid AAV-F Mediates Widespread Transgene Expression in Nonhuman Primate Spinal Cord After Intrathecal Administration. Hum Gene Ther 2021. [PMID: 34128391 DOI: 10.1089/hum.2021.069] [Reference Citation Analysis]
24 Krauze AV, Camphausen K. Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition. Int J Mol Sci 2021;22:13278. [PMID: 34948075 DOI: 10.3390/ijms222413278] [Reference Citation Analysis]
25 Wattenberg MM, Reiss KA. Determinants of Homologous Recombination Deficiency in Pancreatic Cancer. Cancers (Basel) 2021;13:4716. [PMID: 34572943 DOI: 10.3390/cancers13184716] [Reference Citation Analysis]
26 Li F, Yang Y, Wei Y, He P, Chen J, Zheng Z, Bu H. Deep learning-based predictive biomarker of pathological complete response to neoadjuvant chemotherapy from histological images in breast cancer. J Transl Med 2021;19:348. [PMID: 34399795 DOI: 10.1186/s12967-021-03020-z] [Reference Citation Analysis]