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Cited by in F6Publishing
For: 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]
Number Citing Articles
1 Shi Z, Zhu C, Zhang Y, Wang Y, Hou W, Li X, Lu J, Guo X, Xu F, Jiang X, Wang Y, Liu J, Jin M. Deep learning for automatic diagnosis of gastric dysplasia using whole-slide histopathology images in endoscopic specimens. Gastric Cancer 2022. [PMID: 35394573 DOI: 10.1007/s10120-022-01294-w] [Reference Citation Analysis]
2 Schneider L, Laiouar-Pedari S, Kuntz S, Krieghoff-Henning E, Hekler A, Kather JN, Gaiser T, Fröhling S, Brinker TJ. Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review. Eur J Cancer 2022;160:80-91. [PMID: 34810047 DOI: 10.1016/j.ejca.2021.10.007] [Reference Citation Analysis]
3 Zhang F, Su J. Research on Music Classification Technology Based on Deep Learning. Security and Communication Networks 2021;2021:1-8. [DOI: 10.1155/2021/7182143] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 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]
5 Goyal H, Sherazi SAA, Mann R, Gandhi Z, Perisetti A, Aziz M, Chandan S, Kopel J, Tharian B, Sharma N, Thosani N. Scope of Artificial Intelligence in Gastrointestinal Oncology. Cancers (Basel) 2021;13:5494. [PMID: 34771658 DOI: 10.3390/cancers13215494] [Reference Citation Analysis]
6 Dai R, Liu M, Xiang X, Li Y, Xi Z, Xu H. OMICS Applications for Medicinal Plants in Gastrointestinal Cancers: Current Advancements and Future Perspectives. Front Pharmacol 2022;13:842203. [DOI: 10.3389/fphar.2022.842203] [Reference Citation Analysis]
7 Klein S, Duda DG. Machine Learning for Future Subtyping of the Tumor Microenvironment of Gastro-Esophageal Adenocarcinomas. Cancers (Basel) 2021;13:4919. [PMID: 34638408 DOI: 10.3390/cancers13194919] [Reference Citation Analysis]
8 Pantelis AG, Panagopoulou PA, Lapatsanis DP. Artificial Intelligence and Machine Learning in the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms—A Scoping Review. Diagnostics 2022;12:874. [DOI: 10.3390/diagnostics12040874] [Reference Citation Analysis]
9 Gui X, Bazarova A, Del Amor R, Vieth M, de Hertogh G, Villanacci V, Zardo D, Parigi TL, Røyset ES, Shivaji UN, Monica MAT, Mandelli G, Bhandari P, Danese S, Ferraz JG, Hayee B, Lazarev M, Parra-Blanco A, Pastorelli L, Panaccione R, Rath T, Tontini GE, Kiesslich R, Bisschops R, Grisan E, Naranjo V, Ghosh S, Iacucci M. PICaSSO Histologic Remission Index (PHRI) in ulcerative colitis: development of a novel simplified histological score for monitoring mucosal healing and predicting clinical outcomes and its applicability in an artificial intelligence system. Gut 2022;71:889-98. [PMID: 35173041 DOI: 10.1136/gutjnl-2021-326376] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]