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Cited by in F6Publishing
For: Kers J, Bülow RD, Klinkhammer BM, Breimer GE, Fontana F, Abiola AA, Hofstraat R, Corthals GL, Peters-Sengers H, Djudjaj S, von Stillfried S, Hölscher DL, Pieters TT, van Zuilen AD, Bemelman FJ, Nurmohamed AS, Naesens M, Roelofs JJTH, Florquin S, Floege J, Nguyen TQ, Kather JN, Boor P. Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study. Lancet Digit Health 2022;4:e18-26. [PMID: 34794930 DOI: 10.1016/S2589-7500(21)00211-9] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Klepaczko A, Majos M, Stefańczyk L, Ejkefjord E, Lundervold A. Whole kidney and renal cortex segmentation in contrast-enhanced MRI using a joint classification and segmentation convolutional neural network. Biocybernetics and Biomedical Engineering 2022. [DOI: 10.1016/j.bbe.2022.02.002] [Reference Citation Analysis]
2 Arthurs C, Roufosse C. Forging the tools for a computer-aided workflow in transplant pathology. Lancet Digit Health 2022;4:e2-3. [PMID: 34794931 DOI: 10.1016/S2589-7500(21)00254-5] [Reference Citation Analysis]