EEG Datasets
Cross-source consensus on EEG Datasets from 1 sources and 5 claims.
1 sources · 5 claims
Preparation
Where it comes from
Highlighted claims
- The main binary cohort contained 274 subjects, including 180 Alzheimer’s disease patients and 94 healthy controls. — DeepTokenEEG Enhancing Mild Cognitive Impairment and Alzheimers Classification via Tokenized EEG Features
- All datasets used resting-state EEG. — DeepTokenEEG Enhancing Mild Cognitive Impairment and Alzheimers Classification via Tokenized EEG Features
- The study combined five public EEG datasets for binary Alzheimer’s disease versus healthy-control classification. — DeepTokenEEG Enhancing Mild Cognitive Impairment and Alzheimers Classification via Tokenized EEG Features
- Non-AD and non-HC cases were excluded from the main binary analysis. — DeepTokenEEG Enhancing Mild Cognitive Impairment and Alzheimers Classification via Tokenized EEG Features
- BrainLat contributed only retained AD and healthy-control EEG subjects despite containing multiple neurological groups. — DeepTokenEEG Enhancing Mild Cognitive Impairment and Alzheimers Classification via Tokenized EEG Features