Artificial intelligence tool vastly scales up Alzheimer's research: Machine learning tool automates pathologists' work to identify disease markers

Amyloid plaques are clumps of protein fragments in the brains of people with Alzheimer's disease that destroy nerve cell connections. Much like the way Facebook recognizes faces based on captured images, the machine learning tool developed by a team of University of California scientists can "see" if a sample of brain tissue has one type of amyloid plaque or another, and do it very quickly. The findings, published May 15 in Nature Communications, suggest that machine learning can augment the expertise and analysis of an expert neuropathologist. The tool allows them to analyze thousands of times more data and ask new questions that would not be possible with the limited data processing capabilities of even the most highly trained human experts. "We still need the pathologist," said Brittany N. Dugger, PhD, an assistant professor in the UC Davis Department of Pathology and Laboratory Medicine at UC Davis and lead author of the study.