Researchers use machine learning to analyze nocturnal brain waves, identifying early neural alterations and classifying patients into biological subgroups. Key takeaways:Researchers developed an AI methodology that analyzes brain electrical activity during sleep to help detect early signs of Alzheimer’s disease. “Signals were recorded using a series of electrodes placed on the scalp that capture the electrical activity of neurons throughout the night. By cross-referencing this data with key cerebrospinal fluid biomarkers—such as beta-amyloid, phosphorylated tau, total tau, and neurofilament light chain—the algorithm identified three distinct subgroups of Alzheimer’s patients. More in Alzheimer’s & Sleep: