Machine learning detects early brain changes linked to Alzheimer's disease

Worcester Polytechnic Institute (WPI) researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer's disease with nearly 93% accuracy. Their research, published in the journal Neuroscience, also revealed that the anatomical changes, involving loss of brain volume, differ by age and sex.

Early diagnosis of Alzheimer's disease can be difficult because symptoms can be mistaken for normal aging. We found that machine-learning technologies, however, can analyze large amounts of data from scans to identify subtle changes and accurately predict Alzheimer's disease and related cognitive states. This advance has informed Alzheimer's disease research and may lead to methods that could allow doctors to diagnose and treat the disease earlier and more effectively."

Alzheimer's disease is a neurodegenerative disorder that impairs mental functions and ultimately leads to death. An estimated 6.9 million Americans age 65 and older are living with Alzheimer's disease.

Healthy brains contain billions of neurons, the cells that process and transmit signals needed for thought, movement, and other bodily functions. Alzheimer's disease injures neurons, leading to cell death and loss of brain tissue and associated cognitive functions.