Researchers Use AI Methods to 'Redefine' Alzheimer's Disease

Researchers at the University of Pennsylvania's Perelman School of Medicine will work with 11 research centers using a $17.8 million grant from the U.S. National Institute on Aging to find more precise diagnostic biomarkers and drug targets for Alzheimer's disease, reports News-Medical . They will use advanced artificial intelligence (AI) techniques to combine and pinpoint patterns in genetic, imaging, and clinical data from more than 60,000 Alzheimer's patients. "Machine learning can help to combine large datasets and tease out a complex pattern that couldn't be seen before," said Penn Medicine Professor Li Shen. The first goal of the project will be to find a connection between genes, imaging, and clinical symptoms to identify the patterns anticipating Alzheimer's diagnosis and progression and to differentiate subtypes of the disease. "We want to redefine the term 'Alzheimer's disease,'" said Penn Medicine Professor Christos Davatzikos. "The truth is that a treatment that works for one set of patients, may not work for another." The researchers will apply those findings to a predictive model of cognitive decline and disease progression, which can be used to guide treatment for future patients.