医学 AI - arXivDaily 专题

2509.10082 2026-04-13 eess.SP cs.LG 54%

FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep Stage Classification

FetalSleepNet：一种基于频谱均衡域适应的迁移学习框架用于胎儿睡眠阶段分类

Weitao Tang, Johann Vargas-Calixto, Nasim Katebi, Nhi Tran, Sharmony B. Kelly, Gari D. Clifford, Robert Galinsky, Faezeh Marzbanrad

机构 * Department of Biomedical Informatics, Emory University（埃默里大学生物医学信息学系）； Ritchie Centre, Hudson Institute of Medical Research（哈德逊医学研究所里奇中心）； Department of Biomedical Engineering, Georgia Institute of Technology（佐治亚理工学院生物医学工程系）； Department of Obstetrics and Gynaecology, Monash University（莫纳什大学妇产科学系）； Department of Electrical and Computer Systems Engineering, Monash University（莫纳什大学电气与计算机系统工程系）

专题命中健康监测：biomedical(comments,journal_ref)；分类 cs.LG、eess.SP

AI总结本文提出FetalSleepNet，首次利用深度学习对羊胎儿EEG进行睡眠阶段分类，通过迁移学习和频谱均衡域适应策略提升分类准确率，实现自动化睡眠阶段识别，为临床应用提供支持。

Comments 13 pages, 4 tables, 5 figures, submitted to IEEE Journal of Biomedical and Health Informatics

Journal ref IEEE Journal of Biomedical and Health Informatics (Early Access), 2026

1. 健康监测 1 篇

FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep Stage Classification