Is Limited Participant Diversity Impeding EEG-based Machine Learning?
NeutralArtificial Intelligence
The article discusses the challenges faced in applying machine learning to electroencephalography (EEG), particularly focusing on the limited diversity of participant data. This limitation can affect the generalizability and robustness of EEG-based ML models, which are crucial for advancing neuroscientific research and clinical applications. By highlighting these issues, the article emphasizes the need for more diverse training data to improve the effectiveness of machine learning in this field.
— Curated by the World Pulse Now AI Editorial System




