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Assessment of glomerular morphological patterns by deep learning algorithms

BACKGROUND: Compilation of different morphological lesion signatures is characteristic of renal pathology. Previous studies have documented the potential value of artificial intelligence (AI) in recognizing relatively clear-cut glomerular structures and patterns, such as segmental or global sclerosi...

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Detalles Bibliográficos
Autores principales:	Weis, Cleo-Aron, Bindzus, Jan Niklas, Voigt, Jonas, Runz, Marlen, Hertjens, Svetlana, Gaida, Matthias M., Popovic, Zoran V., Porubsky, Stefan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer International Publishing 2022
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8927010/ https://www.ncbi.nlm.nih.gov/pubmed/34982414 http://dx.doi.org/10.1007/s40620-021-01221-9

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