Machine Learning to Predict Cognitive Decline in Alzheimer’s Disease

Machine Learning to Predict Cognitive Decline in Alzheimer’s Disease

Artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to predict disease progression and the probability that people will respond to treatment across a variety of neurologic disorders including Alzheimer’s disease (AD). Ali Ezzati, M.D., has received a five-year, $988,000 grant from the National Institutes of Health to develop new models for predicting cognitive decline in older individuals, people with normal cognition who are at high-risk for developing AD, and patients in preclinical stages of AD such as mild cognitive impairment (MCI).

Dr. Ezzati and his colleagues will apply a novel ML framework to many types of data including clinical, neuropsychological, genetic, and biomarker data. Each type of data will add incremental value to the predictive models, increasing the models’ performance. Findings from this study may lead to development of tool that will improve the ability to identify at-risk individuals, boost power of clinical trials, and increase the probability of their success while reducing associated costs.

Dr. Ezzati is an assistant professor in the Saul R. Korey Department of Neurology at Einstein and is an attending physician at Montefiore Health System.(1K23AG063993-01A1)

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