Exploring the potential of explainable deep learning for EEG-based cognitive decline prediction

Our models achieved state-of-the-art results in the MCI classification task, and demonstrated learning progress in predicting cognitive decline in the preclinical stage. As this is the first time DL models have been evaluated to classify healthy subjects based on cognitive scores, where brain changes are minimal and difficult to detect, this study opens new avenues for discovering biomarkers in early AD diagnosis and facilitating early interventions. Interpretation of the trained DL attention models provided valuable insights that aligned with the existing brain research, serving as a helpful tool for validating AI in healthcare applications.