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Julie Krause, horn

ContributorsKrause, Julie (Performer) / Yu, Wan-Ting (Performer) / Jeon, Dasom (Performer) / ASU Library. Music Library (Publisher)
Created2025-04-11

Studio E 203 voice recital: Students of Amanda DeMaris

ContributorsASU Library. Music Library (Publisher)
Created2025-04-02

Katherine Phillips, horn

ContributorsPhillips, Katherine (Performer) / Glomb, Lauren (Performer) / Templeton, Grace (Performer) / Ritchie, Elizabeth (Performer) / ASU Library. Music Library (Publisher)
Created2025-03-18

Employing ROCKET and Machine Learning on Naturalistic Driving Data to Predict Mild Cognitive Impairment

Description
Alzheimer's disease is a rapidly growing public health crisis. This challenging neurodegenerative disease starts with a prolonged pre-clinical phase, known as Mild Cognitive Impairment. (MCI) Researchers advocate for the importance in diagnosing individuals with MCI to prevent further disease progression. Current diagnostic approaches are not sufficient because they don't capture…

Alzheimer's disease is a rapidly growing public health crisis. This challenging neurodegenerative disease starts with a prolonged pre-clinical phase, known as Mild Cognitive Impairment. (MCI) Researchers advocate for the importance in diagnosing individuals with MCI to prevent further disease progression. Current diagnostic approaches are not sufficient because they don't capture the fluctuant behavior expected with MCI symptoms; consequently, researchers have been exploring how studying lifestyle and routine data of individuals can improve diagnosis accuracy. The goal of this thesis was to contribute towards a working-effort in creating a machine learning model that can supplement the clinical diagnosis of MCI using naturalistic driving data. By implementing a state-of-the-art algorithm known ROCKET with classical machine learning classifiers, my work aims to help design a model that can accurately diagnose individuals with MCI.
ContributorsLimaye, Anushka (Author) / Wu, Teresa (Thesis director) / Forzani, Erica (Committee member) / Al-Hindawi, Firas (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / School of Biological & Health Systems Engineering (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2025-05

Barrett Symphonic Choir pops concert

ContributorsASU Library. Music Library (Publisher)
Created2025-03-25

Gabbie Wong, oboe

ContributorsWong, Gabbie (Performer) / Schuring, Martin (Performer) / Hsieh, Hsiao-Hsi (Performer) / ASU Library. Music Library (Publisher)
Created2025-03-22

Eduardo Martinez, bassoon

ContributorsMartinez, Eddie (Performer) / Yu, Wan-Ting (Performer) / Glomb, Lauren (Performer) / ASU Library. Music Library (Publisher)
Created2025-03-27

Zhelin Li, collaborative piano

ContributorsLi, Zhelin (Performer) / Steinblums, Martins (Performer) / Cao, Yundian (Performer) / Cid, Ramses (Performer) / ASU Library. Music Library (Publisher)
Created2025-04-24

The Big 4, euphonium

ContributorsNolan, Ethan (Performer) / Martin, Steven (Performer) / Sloan, Zachary (Performer) / DiMillio, Rocco (Performer) / ASU Library. Music Library (Publisher)
Created2025-02-25

"Fullness of Joy" Tiffany Steinweg, violin

ContributorsSteinweg, Tiffany (Performer) / Wang, Chuwen (Performer) / ASU Library. Music Library (Publisher)
Created2025-02-23