Künstliche Intelligenz in der Nierentransplantationspathologie-Reference-Cited by-同舟云学术

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Künstliche Intelligenz in der Nierentransplantationspathologie

Published:2024-04-10 Issue:4 Volume:45 Page:277-283
ISSN:2731-7188
Container-title:Die Pathologie
language:de
Short-container-title:Pathologie

Author:

Bülow Roman David,Lan Yu-Chia,Amann Kerstin,Boor Peter^ORCID

Funder

Deutsche Forschungsgemeinschaft

HORIZON EUROPE European Research Council

Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie

Innovationsfond des Gemeinsamen Bundesausschusses

Medizinische Fakultät der RWTH Aachen

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00292-024-01324-7.pdf

Reference28 articles.

1. Bülow RD, Hölscher DL, Costa IG, Boor P (2023) Extending the landscape of omics technologies by pathomics. NPJ Syst Biol Appl 9:38

2. Choi G, Kim Y‑G, Cho H et al (2020) Automated detection algorithm for C4d immunostaining showed comparable diagnostic performance to pathologists in renal allograft biopsy. Mod Pathol 33:1626–1634

3. Farris AB, Vizcarra J, Amgad M et al (2021) Image Analysis Pipeline for Renal Allograft Evaluation and Fibrosis Quantification. Kidney Int Rep 6:1878–1887

4. Ghaffari Laleh N, Truhn D, Veldhuizen GP et al (2022) Adversarial attacks and adversarial robustness in computational pathology. Nat Commun 13:5711

5. Hermsen M, de Bel T, den Boer M et al (2019) Deep Learning-Based Histopathologic Assessment of Kidney Tissue. J Am Soc Nephrol 30:1968–1979

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