校正: 机器学习用于检测社会焦虑障碍,使用有效的连接和图形理论措施
Abdulhakim Al-Ezzi1, Nidal Kamel2, Amal A Al-Shargabi3
1Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia.
Frontiers in psychiatry
|August 9, 2023
概括
这项研究纠正了先前发表的一篇文章. 修正涉及研究的数字物体标识符 (DOI).
科学领域:
- 精神病学是一个精神病学.
- 神经科学是一个神经科学.
背景情况:
- 之前的一篇文章DOI被错误发布.
- 准确的引用对于科学完整性和可重复性至关重要.
研究的目的:
- 纠正已发表文章的数字物体标识符 (DOI).
- 确保研究的适当引用和可访问性.
主要方法:
- 发布了一份纠正通知.
- 正确的DOI被确定并公布.
主要成果:
- 文章DOI已经被纠正.
- 以前的DOI现在已经过时了.
结论:
- 校正有助于准确检索研究文章.
- 确保正确的DOI支持科学记录.
关键词:
这是一个EEGEEGEEGEEGEEGEEGEEG.有效的连接,有效的连接.与事件相关的潜在事件.图形理论分析分析图形理论分析机器学习是机器学习.部分定向的连贯性 部分定向的连贯性社会焦虑症 社交焦虑症 社交焦虑症支持矢量机器的支持矢量机器更多相关视频
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