UTA engineer to use deep learning tools to identify types of dementia linked to Alzheimer’s disease

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A computer engineer from the University of Texas at Arlington will advance and integrate powerful deep learning methods and tools to identify types of Alzheimer’s disease-related dementias (ADRD), which could help the medical community to better treat these diseases.

Dajiang Zhu, an assistant professor in the Department of Computer Science and Engineering, will lead a five-year, $2.86 million project supported by the National Institute of Neurological Disorders and Stroke (NINDS). Zhu will collaborate with researchers from the University of North Carolina-Chapel Hill and the University of Georgia to focus on developing a deep learning model for SARD analysis.

As the two most common types of dementia, Alzheimer’s disease and Lewy body dementias (LBDs) account for 65% to 85% of people with dementia nationwide, or about 7.5 million people.

Zhu said there are important differences in determining whether a patient has Alzheimer’s disease or LBD. These differences can greatly influence the type of treatment they are prescribed. However, differentiating between Alzheimer’s and LBD is difficult due to both mixed pathologies and clinical symptoms.

In this project, we will discover, define and represent individual GyralNets; a computational model that incorporates both deep learning methods and neuroimaging markers; to characterize Alzheimer’s disease/LBD-related abnormalities in individual patients,”


Dajiang Zhu, Assistant Professor, Department of Computer Science and Engineering, University of Texas at Arlington

He added that the project will eventually assemble, map and analyze large-scale brain data for practical clinical settings.

“Ultimately, we want to characterize and summarize the deep relationships within the brain that will lead to improved predictive ability between Alzheimer’s disease and LBD,” Zhu said. “We believe that earlier recognition of the specific disease present may lead to better outcomes through better treatment for these patients.”

Hong Jiang, Wendell H. Nedderman Endowed Professor and chair of the computer science and engineering department, said Zhu’s research has the potential to have significant impact.

“Taking all the data that can be accumulated and using it in a way that will help society and people suffering from these diseases is monumental,” Jiang said. “He represents what university research is all about.”

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University of Texas at Arlington

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