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Updated: Jun 8, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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在急性缺血性中风中使用融合成像和临床深度学习模型预测功能性结果

Yongkai Liu1, Yannan Yu1, Jiahong Ouyang1,2

  • 1Department of Radiology (Y.L., Y.Y., J.O., B.J., S.O., G.Z.).

Stroke
|July 24, 2023
PubMed
概括

预测急性缺血性中风的结果至关重要. 一个融合成像和临床数据的深度学习模型准确地预测了长期修改的兰金级分数,改善了预后.

关键词:
目标目标目标目标目标目标目标心脏病发作的心脏病发作缺血性中风 中风磁共振成像技术的使用人们的生活质量.

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