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Updated: Feb 14, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
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一个混合LSTM-GRU框架用于肺癌分类,使用GWO-WOA算法进行超参数调整和BPSO进行特征选择

Mohmod M Sh Amrir1, Yasser M Ayid2, Ahmed M Elshewey3,4

  • 1Industrial and System Engineering, Collage of Engineering, University of Jeddah, Jeddah, Saudi Arabia. mamrir@uj.edu.sa.

Scientific reports
|February 12, 2026
PubMed
概括

本研究引入了一种优化的混合深度学习模型,用于使用问卷数据进行早期肺癌检测. 先进的框架实现了近乎完美的准确性,为临床风险分层提供了一个强大的工具.

关键词:
二元粒子小群优化二元粒子小群优化深度学习是一种深度学习.在这里,GRU GRU GRU医疗保健 医疗保健 医疗保健 医疗保健超参数调整 超参数调整这是LSTM的LSTM.在LSTM-GRU中.肺癌是一种肺癌.肺癌的分类 肺癌的分类

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