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Updated: Jun 28, 2025

Nasal Brushing Sampling and Processing Using Digital High Speed Ciliary Videomicroscopy – Adaptation for the COVID-19 Pandemic
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Published on: November 7, 2020

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基于修剪的过量采样技术,用于对Covid-19不平衡的临床数据集进行光滑的启动重新采样

Prasetyo Wibowo1, Chastine Fatichah1

  • 1Department of Informatics, Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.

Journal of King Saud University. Computer and information sciences
|April 15, 2024
PubMed
概括

一种新的过量采样技术,TRIM-SBR,有效地解决了COVID-19预测模型中的数据不平衡. 这种方法通过生成合成少数类数据来提高诊断准确性,优于现有技术.

关键词:
在 COVID-19 疫情中,不平衡的数据不平衡的数据机器学习 机器学习过量采样过度采样平滑的启动链重新采样.

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