AI Machine Learning Predicts Alzheimer's Disease Risk

The most common cause of dementia worldwide is Alzheimer's disease (AD), a neurodegenerative disorder with no known cure. A new study published in Scientific Reports uses artificial intelligence (AI) machine learning (ML) and data from electronic health records (EHRs) to identify the important predictors for Alzheimer's disease and finds that a person's genetics outperforms age as a predictor for individuals who are 65 years of age and older. "Machine learning (ML) methods provide an attractive and effective alternative to traditional statistical regression models, especially in situations where one has a large number of features or predictors," wrote the authors of the National Institutes of Health (NIH) funded study led by Xiaoyi Raymond Gao at The Ohio State University College of Medicine, with Ohio State researchers Marion Chiariglione, Ke Qin and Douglas Scharre; the University of Miami researchers Karen Nuytemans and Eden Martin; and Yi-Ju Li at Duke University. Globally, Alzheimer's disease accounts for an estimated 60-70 percent of the over 55 million people with dementia and affects women disproportionately according to the World Health Organization (WHO). In the U.S., there are currently 6.7 million people aged 65 and older with living AD, of which almost two-thirds are women and that figure will increase significantly to an estimated 12.7 million Americans by 2050 according to the Alzheimer's Association.