Development and validation of an endoscopic diagnostic model for sessile serrated lesions based on machine learning algorithms
Background and aimsSessile serrated lesions (SSLs) are morphologically subtle and often misclassified as hyperplastic polyps (HPs), increasing colorectal cancer risks. We developed a machine learning (ML) model to improve endoscopic SSL diagnosis.MethodsThree hundred and eighty-six colorectal polyps...
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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: |
Frontiers Media S.A.
2025-10-01
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| シリーズ: | Frontiers in Medicine |
| 主題: | |
| オンライン･アクセス: | https://www.frontiersin.org/articles/10.3389/fmed.2025.1665079/full |
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