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Currently, memory tests are the most common method for diagnosing Alzheimer’s disease. The problem? Alzheimer’s can start affecting the mind decades before the first noticeable symptoms surface. To spot signs of the disease earlier, USC researchers are using new machine learning methods to study how clusters of certain biological traits influence a patient’s likelihood of developing Alzheimer’s. Click the link below to see how neuroscientist Paul Thompson and computer scientist Greg Ver Steeg are collaborating to improve Alzheimer’s detection.


USC Researchers Use AI to Detect Early Signs of Alzheimer’s

Michael Cox

Michael was born and raised in a small island town off the coast of Seattle. He went to USC, but he’s still a Pacfic Northwesterner at heart—he loves hiking, reading, and watching the Seattle sports teams disappoint him. At Viterbi, Michael counsels high school and transfer students in the application process.

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