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Updated: Jul 15, 2025

Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research
04:54

Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research

Published on: November 8, 2024

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在多模式时间序列上优化睡眠分阶段:利用边界合成少数群体过量抽样技术和监督的卷积对比学习

Xinyu Huang1, Franziska Schmelter2, Muhammad Tausif Irshad1

  • 1Institute of Medical Informatics, University of Lübeck, Germany.

Computers in biology and medicine
|September 24, 2023
PubMed
概括

一种新的方法,边界合成少数群体过量采样技术 (B-SMOTE) 基于监督卷积对比学习 (BST-SCCL),提高了睡眠阶段分类的准确性. 这种方法有效地解决了睡眠数据中的阶级不平衡,以改善健康洞察力.

关键词:
在B-SMOTE中使用.生物信号处理 生物信号处理跨领域的适应.多模式的多睡眠学.剩余网络的残余网络睡眠阶段的分类 睡眠阶段的分类监督的对比学习学习截断的交叉缩率 截断的交叉缩率

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