Imperial College London（帝国理工学院）

Affect and Effect: Limitations of regularisation-based continual learning in EEG-based emotion classification

情感与影响：基于EEG情感分类的正则化连续学习的局限性

Nina Peire, Yupei Li, Björn Schuller

机构 * Imperial College London（帝国理工学院伦敦分校） 纠错

AI总结 本研究发现基于正则化的连续学习方法在EEG情感分类中存在局限性，主要由于稳定性与可塑性之间的权衡问题。

Comments 20 pages, 16 figures, not including Appendix. Code can be found at: https://github.com/glam-imperial/AffectEffect

An AI-driven framework for the prediction of personalised health response to air pollution

面向空气污染的个性化健康响应预测的AI驱动框架

Nazanin Zounemat-Kermani, Sadjad Naderi, Claire H. Dilliway, Claire E. Heaney, Shrreya Behll, Boyang Chen, Hisham Abubakar-Waziri, Alexandra E. Porter, Marc Chadeau-Hyam, Fangxin Fang, Ian M. Adcock, Kian Fan Chung, Christopher C. Pain

机构 * organization= Data Science Institute, Imperial College London , country= UK ； organization= Department of Earth Science \& Engineering, Imperial College London , country= UK ； organization= Centre for AI-Physics Modelling, Imperial-X, Imperial College London , country= UK ； organization= National Heart \& Lung Institute, Imperial College London , country= UK ； organization= Department of Materials, Imperial College London , country= UK ； organization= MRC/PHE Centre for Environment ； Health, School of Public Health, Imperial College London , country= UK 纠错

AI总结 本文提出一个基于AI的框架，通过整合可穿戴设备数据和实时环境数据，预测个人对空气污染的健康响应，展示了个性化环境健康监测的可行性。

Comments Zounemat-Kermani and Naderi share first authorship. 22 pages, 5 figures and 1 table