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Deep learning outperforms kidney organoid experts

Detalles Bibliográficos
Autores principales: Yu, Seyoung, Gee, Heon Yung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Nephrology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902735/
https://www.ncbi.nlm.nih.gov/pubmed/36747356
http://dx.doi.org/10.23876/j.krcp.22.174
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author Yu, Seyoung
Gee, Heon Yung
author_facet Yu, Seyoung
Gee, Heon Yung
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spelling pubmed-99027352023-02-16 Deep learning outperforms kidney organoid experts Yu, Seyoung Gee, Heon Yung Kidney Res Clin Pract Editorial The Korean Society of Nephrology 2023-01 2023-01-31 /pmc/articles/PMC9902735/ /pubmed/36747356 http://dx.doi.org/10.23876/j.krcp.22.174 Text en Copyright © 2023 The Korean Society of Nephrology https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial and No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ) which permits unrestricted non-commercial use, distribution of the material without any modifications, and reproduction in any medium, provided the original works properly cited.
spellingShingle Editorial
Yu, Seyoung
Gee, Heon Yung
Deep learning outperforms kidney organoid experts
title Deep learning outperforms kidney organoid experts
title_full Deep learning outperforms kidney organoid experts
title_fullStr Deep learning outperforms kidney organoid experts
title_full_unstemmed Deep learning outperforms kidney organoid experts
title_short Deep learning outperforms kidney organoid experts
title_sort deep learning outperforms kidney organoid experts
topic Editorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902735/
https://www.ncbi.nlm.nih.gov/pubmed/36747356
http://dx.doi.org/10.23876/j.krcp.22.174
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