Comment on: "Artificial Intelligence Can Facilitate Application of Risk Stratification Algorithms to Bladder Cancer Patient Case Scenarios".
作者信息
Daungsupawong Hinpetch, Wiwanitkit Viroj
出版信息
Clin Med Insights Oncol. 2025 Jul 6;19:11795549251350242. doi: 10.1177/11795549251350242. eCollection 2025.
Abstract
摘要
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AI allows pre-screening of FGFR3 mutational status using routine histology slides of muscle-invasive bladder cancer.人工智能可利用肌肉浸润性膀胱癌的常规组织学切片对成纤维细胞生长因子受体3（FGFR3）突变状态进行预筛查。
Nat Commun. 2024 Dec 30;15(1):10914. doi: 10.1038/s41467-024-55331-6.
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Towards interactive AI-authoring with prototypical few-shot classifiers in histopathology.迈向在组织病理学中使用原型少样本分类器进行交互式人工智能创作。
J Pathol Inform. 2024 Jun 6;15:100388. doi: 10.1016/j.jpi.2024.100388. eCollection 2024 Dec.
3
Artificial Intelligence can Facilitate Application of Risk Stratification Algorithms to Bladder Cancer Patient Case Scenarios.人工智能可促进风险分层算法在膀胱癌患者病例场景中的应用。
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The Prognostic Significance of Histological Subtypes in Patients with Muscle-Invasive Bladder Cancer: An Overview of the Current Literature.组织学亚型在肌层浸润性膀胱癌患者中的预后意义：当前文献综述
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Eur Urol Focus. 2022 Mar;8(2):457-464. doi: 10.1016/j.euf.2021.04.005. Epub 2021 Apr 16.
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