Development and validation of an artificial intelligence-based model for detecting urothelial carcinoma using urine cytology images: a multicentre, diagnostic study with prospective validationResearch in context
Summary: Background: Urine cytology is an important non-invasive examination for urothelial carcinoma (UC) diagnosis and follow-up. We aimed to explore whether artificial intelligence (AI) can enhance the sensitivity of urine cytology and help avoid unnecessary endoscopy. Methods: In this multicent...
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| 主要な著者: | , , , , , , , , , , , , , , , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Elsevier
2024-05-01
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| シリーズ: | EClinicalMedicine |
| 主題: | |
| オンライン・アクセス: | http://www.sciencedirect.com/science/article/pii/S2589537024001457 |
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