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Updated: Jun 23, 2026

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

一个BiLSTM模型增强了多目标算术优化,用于从CT图像中诊断COVID-19

Liang Chen1, Xin Lin2, Liangliang Ma2

  • 1Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Yijishan Hospital of Wannan Medical College, Wuhu, 241000, China.

Scientific reports
|March 29, 2025
PubMed
概括

这项研究引入了一种使用多目标优化算法 (MOAOA) 的新型人工智能方法,以提高从CT扫描中诊断COVID-19的准确性. 增强的BiLSTM模型实现了高精度和特异性,优于现有方法.

关键词:
自动诊断 自动诊断这就是BiLSTM.在 COVID-19 疫情中,莫阿阿阿阿 莫阿阿阿多目标优化多目标优化

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