Association of Pathological Fibrosis With Renal Survival Using Deep Neural Networks

Association of Pathological Fibrosis With Renal Survival Using Deep Neural Networks

Chronic kidney damage is routinely assessed semiquantitatively by scoring the amount of fibrosis and tubular atrophy in a renal biopsy sample. Although image digitization and morphometric techniques can better quantify the extent of histologic damage, we need more widely applicable ways to stratify...

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Bibliographic Details
Main Authors: Vijaya B. Kolachalama, Priyamvada Singh, Christopher Q. Lin, Dan Mun, Mostafa E. Belghasem, Joel M. Henderson, Jean M. Francis, David J. Salant, Vipul C. Chitalia
Format: Article
Language:English
Published: Elsevier 2018-03-01
Series:Kidney International Reports
Subjects:
histology
machine learning
renal fibrosis
renal survival
Online Access:http://www.sciencedirect.com/science/article/pii/S2468024917304370

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http://www.sciencedirect.com/science/article/pii/S2468024917304370

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