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Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects
BACKGROUND: Optimal detection and surveillance of bladder cancer (BCa) rely primarily on the cystoscopic visualization of bladder lesions. AI-assisted cystoscopy may improve image recognition and accelerate data acquisition. OBJECTIVE: To provide a comprehensive review of machine learning (ML), deep...
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| Опубликовано в: : | World J Urol |
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| Главные авторы: | , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer Berlin Heidelberg
2020
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7508959/ https://ncbi.nlm.nih.gov/pubmed/31925551 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00345-019-03059-0 |
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