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Updated: Jun 11, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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在多类图像分类中使用COVID-19和肺炎的胸部X射线图像来量化不确定性

Albert Whata1, Katlego Dibeco1, Kudakwashe Madzima2

  • 1Department of Mathematical Sciences, Sol Plaatje University, Kimberley, South Africa.

Frontiers in artificial intelligence
|October 3, 2024
PubMed
概括

与传统贝叶斯神经网络相比,具有不确定性量化 (UQ) 的深度神经网络,特别是贝叶斯神经网络集团和蒙特卡洛脱落集团,在对COVID-19,肺炎和正常病例的胸部X射线分类方面表现出卓越的性能.

关键词:
贝叶斯神经网络是一个贝叶斯神经网络.蒙特卡洛合唱团 蒙特卡洛合唱团蒙特卡洛学的人胸部X射线 - 胸部X射线 - 胸部X射线分类指标分类指标.多个类别的分类分类.不确定性量化深度神经网络的神经网络.

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