Assessment of glomerular morphological patterns by deep learning algorithms.
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| Title: | Assessment of glomerular morphological patterns by deep learning algorithms. |
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| Authors: | Weis CA; Institute of Pathology, University Medical Centre Mannheim, University of Heidelberg, 68167, Mannheim, Germany. cleo-aron.weis@medma.uni-heidelberg.de., Bindzus JN; Institute of Pathology, University Medical Centre Mannheim, University of Heidelberg, 68167, Mannheim, Germany., Voigt J; Institute of Pathology, University Medical Centre Mannheim, University of Heidelberg, 68167, Mannheim, Germany., Runz M; Institute of Pathology, University Medical Centre Mannheim, University of Heidelberg, 68167, Mannheim, Germany.; Mannheim Institute for Intelligent Systems in Medicine, University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany., Hertjens S; Institute of Medical Statistics and Biometry, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany., Gaida MM; Institute of Pathology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany., Popovic ZV; Institute of Pathology, University Medical Centre Mannheim, University of Heidelberg, 68167, Mannheim, Germany., Porubsky S; Institute of Pathology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany. stefan.porubsky@unimedizin-mainz.de. |
| Source: | Journal of nephrology [J Nephrol] 2022 Mar; Vol. 35 (2), pp. 417-427. Date of Electronic Publication: 2022 Jan 04. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: Italy NLM ID: 9012268 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1724-6059 (Electronic) Linking ISSN: 11218428 NLM ISO Abbreviation: J Nephrol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1724-6059 |
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| DOI: | 10.1007/s40620-021-01221-9 |
