UNMC (www.unmc.edu) researchers, along with national and international leaders, recently published a study on identifying dementia through deep learning computer models. The study, “Multimodal deep learning for Alzheimer’s disease dementia assessment,” published in the highly recognized Nature Communications journal, looked at persons with normal cognition, mild cognitive impairment, Alzheimer’s disease, and non-AD dementias and ways to improve the diagnosis.
The team from the UNMC Department of Neurological Sciences included Daniel Murman, MD, Arun Swaminathan, MD, Olga Taraschenko, MD, PhD, and former colleague Sachin Kedar, MD, MBBS. The group, using routinely collected clinical information such as MRI scans, demographics, medical history, functional assessments, and neuropsychological tests, developed deep learning models on various classification tasks.
The interpretability methods using artificial intelligence modeling showed high accuracy in disease-specific patterns of degenerative changes throughout the brain that closely correspond to neuropathological lesions at autopsy.
Drs. Swaminathan, Murman, and Taraschenko were among the clinicians who reviewed and validated neuropsychological assessments, patients’ histories, and their imaging studies that were compared to the machine learning models developed in the study. The project was supported by grants from the Karen Toffler Charitable Trust, the Michael J. Fox Foundation, the Lewy Body Dementia Association, the Alzheimer’s Drug Discovery Foundation, the American Heart Association and the National Institutes of Health.
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