Awardee Organization(s): University of Washington
Principal Investigator(s): Mehmet Kurt, PhD
Official Project Title: An explainable deep learning framework for brain age prediction in AD
AITC Partner: PennAITech
Website(s): https://www.me.washington.edu/facultyfinder/mehmet-kurt
The biology of aging is a complex biological process that has yet to be fully understood. Recently, due to the growth in data availability and advances in deep learning techniques, brain age has been demonstrated as an effective biomarker for studying the brain aging process in the presence and absence of neurological disorders. This “brain age” provides a global estimate of how the subject’s brain deviates from the average brain of a similar age. In the PennAITech project, we will extend brain age predictions to brain anatomy by providing age for different brain regions. We will also improve the transparency and accountability of this tool by explaining brain age in terms of clinically relevant image features, e.g., explaining brain age by highlighting brain regions that indicate accelerated aging. By identifying individual patterns of brain aging and specific areas of accelerated aging, clinicians using this tool can tailor individualized interventions and prognostic strategies. This subject-specific approach can improve outcomes by addressing specific risk factors and vulnerabilities.
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