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For: Wulczyn E, Steiner DF, Moran M, Plass M, Reihs R, Tan F, Flament-Auvigne I, Brown T, Regitnig P, Chen PC, Hegde N, Sadhwani A, MacDonald R, Ayalew B, Corrado GS, Peng LH, Tse D, Müller H, Xu Z, Liu Y, Stumpe MC, Zatloukal K, Mermel CH. Interpretable survival prediction for colorectal cancer using deep learning. NPJ Digit Med 2021;4:71. [PMID: 33875798 DOI: 10.1038/s41746-021-00427-2] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Martin B, Grosser B, Kempkens L, Miller S, Bauer S, Dhillon C, Banner BM, Brendel EM, Sipos É, Vlasenko D, Schenkirsch G, Schiele S, Müller G, Märkl B. Stroma AReactive Invasion Front Areas (SARIFA)-A New Easily to Determine Biomarker in Colon Cancer-Results of a Retrospective Study. Cancers (Basel) 2021;13:4880. [PMID: 34638364 DOI: 10.3390/cancers13194880] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Yao J, Shi Y, Cao K, Lu L, Lu J, Song Q, Jin G, Xiao J, Hou Y, Zhang L. DeepPrognosis: Preoperative prediction of pancreatic cancer survival and surgical margin via comprehensive understanding of dynamic contrast-enhanced CT imaging and tumor-vascular contact parsing. Med Image Anal 2021;73:102150. [PMID: 34303891 DOI: 10.1016/j.media.2021.102150] [Reference Citation Analysis]
3 Chen SB, Novoa RA. Artificial intelligence for dermatopathology: Current trends and the road ahead. Seminars in Diagnostic Pathology 2022. [DOI: 10.1053/j.semdp.2022.01.003] [Reference Citation Analysis]
4 Grosser B, Glückstein MI, Dhillon C, Schiele S, Dintner S, VanSchoiack A, Kroeppler D, Martin B, Probst A, Vlasenko D, Schenkirsch G, Märkl B. Stroma AReactive Invasion Front Areas (SARIFA) - a new prognostic biomarker in gastric cancer related to tumor-promoting adipocytes. J Pathol 2021. [PMID: 34580877 DOI: 10.1002/path.5810] [Reference Citation Analysis]
5 Shimpi N, Glurich I, Rostami R, Hegde H, Olson B, Acharya A. Development and Validation of a Non-Invasive, Chairside Oral Cavity Cancer Risk Assessment Prototype Using Machine Learning Approach. JPM 2022;12:614. [DOI: 10.3390/jpm12040614] [Reference Citation Analysis]
6 Lin A, Qi C, Li M, Guan R, Imyanitov EN, Mitiushkina NV, Cheng Q, Liu Z, Wang X, Lyu Q, Zhang J, Luo P. Deep Learning Analysis of the Adipose Tissue and the Prediction of Prognosis in Colorectal Cancer. Front Nutr 2022;9:869263. [DOI: 10.3389/fnut.2022.869263] [Reference Citation Analysis]
7 Ding D, Lang T, Zou D, Tan J, Chen J, Zhou L, Wang D, Li R, Li Y, Liu J, Ma C, Zhou Q. Machine learning-based prediction of survival prognosis in cervical cancer. BMC Bioinformatics 2021;22:331. [PMID: 34134623 DOI: 10.1186/s12859-021-04261-x] [Reference Citation Analysis]
8 Gamble P, Jaroensri R, Wang H, Tan F, Moran M, Brown T, Flament-auvigne I, Rakha EA, Toss M, Dabbs DJ, Regitnig P, Olson N, Wren JH, Robinson C, Corrado GS, Peng LH, Liu Y, Mermel CH, Steiner DF, Chen PC. Determining breast cancer biomarker status and associated morphological features using deep learning. Commun Med 2021;1. [DOI: 10.1038/s43856-021-00013-3] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
9 Li X, Jonnagaddala J, Yang S, Zhang H, Xu XS. A retrospective analysis using deep-learning models for prediction of survival outcome and benefit of adjuvant chemotherapy in stage II/III colorectal cancer. J Cancer Res Clin Oncol 2022. [PMID: 35332389 DOI: 10.1007/s00432-022-03976-5] [Reference Citation Analysis]
10 Müller H, Holzinger A, Plass M, Brcic L, Stumptner C, Zatloukal K. Explainability and Causability for Artificial Intelligence-Supported Medical Image Analysis in the Context of the European In Vitro Diagnostic Regulation. New Biotechnology 2022. [DOI: 10.1016/j.nbt.2022.05.002] [Reference Citation Analysis]