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Updated: Jul 27, 2025

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数据分布对瘤细分中的联合学习表现的影响

Guibo Luo1, Tianyu Liu1, Jinghui Lu1

  • 1From the Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, 400C, Boston, MA 02114 (G.L., T.L., J.L., W.C.); Intel Corporation, Santa Clara, Calif (X.C.); Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong (L.Y.); College of Computer Science and Technology, Zhejiang University, Hangzhou, China (J.W.); and Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Ind (D.Z.C.).

Radiology. Artificial intelligence
|June 9, 2023
PubMed
概括

联合深度学习 (Fed-DL) 在瘤细分中的表现受到数据分布差异的负面影响. 较大的数据分布距离导致CT和MR图像上的Fed-DL模型性能降低.

关键词:
腹部/食谱/地理标志物大脑/大脑干这就是为什么CTCTCTCTCTCT进行比较研究.卷积神经网络 (CNN) 是一种神经网络.数据的分布数据的分布.联合深度学习 (Deep Learning) 是一个联合的深度学习 (Deep Learning).肝脏 肝脏 肝脏 肝脏在MR成像中使用MR成像.瘤细分 瘤细分

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