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Nicole Ball’s MS in Statistics Project Presentation “Detecting Alzheimer’s Disease in MRIs Using Convolutional Neural Networks”

Friday, Apr 26th @ 11 a.m. - 1 p.m.

Join us for Nicole Ball’s MS in Statistics Project Presentation “Detecting Alzheimer’s Disease in MRIs Using Convolutional Neural Networks” Friday April 26th at 11 am in Student Commons 4113 or on Zoom. Email mathstats-staff@ucdenver.edu for the Zoom link.

 

Title: Detecting Alzheimer’s Disease in MRIs Using Convolutional Neural Networks

Abstract: Early detection of Alzheimer’s Disease can assist in providing a longer, more independent life. Underserved groups in the community, such as minorities and those without college degrees, are at the highest risk of developing Dementia, and they tend to have the least time and money to spend on it. Automating the diagnosis process could speed it up, cost less, and get the patient on a plan to slow the disease progression sooner. This study uses convolutional neural networks to analyze three MRI views of the brain: coronal, axial, and sagittal. The models maximize recall without depleting the F1 score. The three convolutional neural networks are combined to produce one prediction on whether the patient has Alzheimer’s Disease or not. This model is the first step in automating the diagnosis of Alzheimer’s Disease. This automation could begin to close the gap between those groups disenfranchised medically and the rest of the people living in the United States.