Emotional recognition through EEG signals is becoming increasingly popular. However, It has been difficult to improve the emotional recognition effect of cross-subjects. In the exploration of cross-subjects proposed in previous works, the effect of the two-category cross-subject emotion recognition should be improved. Therefore, it is necessary to propose a method for improving the accuracy of […]

Alzheimer’s disease (AD) patients are known to have heterogeneous clinical presentation and pathologic patterns. We hypothesize that AD dementia can be categorized into subtypes based on multimodal imaging biomarkers such as magnetic resonance imaging (MRI), tau positron emission tomography (PET), and amyloid PET. We collected 3T MRI, 18F-THK5351 PET, and 18F-flutemetamol (FLUTE) PET data from […]

Deep learning, a state-of-the-art machine learning approach, has shown outstanding performance over traditional machine learning in identifying intricate structures in complex high-dimensional data, especially in the domain of computer vision. The application of deep learning to early detection and automated classification of Alzheimer’s disease (AD) has recently gained considerable attention, as rapid progress in neuroimaging […]