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Updated: Jul 12, 2025

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一个进化机器学习多发性骨髓瘤使用Runge Kutta优化器从多特征索引的进化机器学习

Yazhou Ji1, Beibei Shi2, Yuanyuan Li1

  • 1Department of Hematology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.

Computers in biology and medicine
|October 20, 2023
PubMed
概括

这项研究介绍了MSRUN-KELM,这是一种新的机器学习框架,用于使用多特征索引诊断多发性骨髓瘤 (MM). MSRUN-KELM实现了高精度,为MM诊断提供了潜在的新工具.

关键词:
功能选择 功能选择核心极端学习机器学习的核心.多特征指数的多特征指数多发性骨髓瘤是一种多发性骨髓瘤.参数优化的参数优化荣格库塔优化器的优化器泥模具学习操作员操作员学习

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