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Updated: Jun 21, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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脏评分监测:使用MRI预测清细胞细胞癌生长的预测机器学习模型

Pouria Yazdian Anari1, Aryan Zahergivar1, Nikhil Gopal2

  • 1Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892-1109, USA.

Abdominal radiology (New York)
|February 12, 2024
PubMed
概括

机器学习模型可以预测Von Hippel-Lindau (VHL) 综合征患者的清细胞细胞癌 (ccRCC) 增长率. 这有助于个性化瘤监测和手术规划VHL相关的ccRCC.

关键词:
清细胞脏细胞癌.决策树 决策树是一个决策树.·希佩尔·林达乌 在

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Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...