New learning-based tool can help predict progression of Alzheimer’s disease

Over 55 million people worldwide are living with dementia, according to the World Health Organization, with Alzheimer’s disease as the most common form.

Researchers from the University of Texas at Arlington said that in addition to physical effects, Alzheimer’s causes psychological, social and economic ramifications not only for the people living with the disease, but also for those who love and care for them.

As Alzheimer’s disease symptoms worsen over time, it is important for patients and their caregivers to prepare for the eventual need to increase the amount of support as the disease progresses.

The novel learning-based framework aims to help pinpoint where patients are within the disease-development spectrum, to best predict the timing of potential later stages, to make it easier to plan for future care as the disease advances.

In a statement, Dajiang Zhu, associate Professor in computer science and engineering at UTA and lead-author, said: “For decades, a variety of predictive approaches have been proposed and evaluated in terms of the predictive capability for Alzheimer’s disease and its precursor, mild cognitive impairment.