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Assessing kidney stone composition using smartphone microscopy and deep neural networks
OBJECTIVES: To propose a point‐of‐care image recognition system for kidney stone composition classification using smartphone microscopy and deep convolutional neural networks. MATERIALS AND METHODS: A total of 37 surgically extracted human kidney stones consisting of calcium oxalate (CaOx), cystine,...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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John Wiley and Sons Inc.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9231678/ https://www.ncbi.nlm.nih.gov/pubmed/35783589 http://dx.doi.org/10.1002/bco2.137 |