Early Alzheimer

Early Alzheimer's disease (EAD) research focuses on developing accurate and timely diagnostic tools to improve patient outcomes. Current efforts leverage machine learning, particularly deep convolutional neural networks and other AI techniques, applied to neuroimaging data (MRI, PET) and even voice biomarkers to identify subtle early-stage indicators of the disease. These models aim to improve diagnostic accuracy and potentially predict disease progression, facilitating earlier interventions. The ultimate goal is to translate these advancements into clinically useful tools for earlier and more effective diagnosis and management of EAD.