Researchers have found a way to precisely detect one of the hallmarks of Alzheimer's disease in human brain tissue with the help of computer using artificial intelligence (AI). According to a study, published Nature Communications journal, is a proof of concept for a computer-learning approach to distinguishing main markers of the neurodegenerative disease.

Amyloid plaques are clumps of protein fragments found in the brains of Alzheimer's disease patients that destroy nerve cell connections, stated researchers at the University of California in the United States. The way the social media app Facebook recognises faces based on captured images, the computer learning tool can detect if a sample of brain tissue has one type of amyloid plaque or another. The findings suggest that computer learning can augment the analysis and expertise of an expert neuropathologist. The tool allows to analyse 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.
According to Brittany N Dugger, an assistant professor at the UC Davis, and lead author of the study stated, "We still need the pathologist. This is a tool, like a keyboard is for writing. As keyboards have aided in writing workflows, digital pathology paired with machine learning can aid with neuropathology workflows."