Title : Machine Learning, Music, and Medicine
Abstract: Recent developments in machine learning allow for high-resolution and data-driven multimodal approaches to the development and deployment of adaptive technologies and music-based therapeutic interventions for a wide variety of disabilities and diseases. There is a wealth of behavioral data that correlates participation in musical activities to improved lucidity, memory, emotional regulation, social interaction, and overall well-being for patients with neurodegenerative diseases, though the precise mechanism of action is as of yet not well-understood. This talk explores three different nascent research projects aimed at leveraging various integrative approaches to understanding music cognition and creativity to not only better understand the effects of musical stimuli (whether patient-directed or patient-initiated) on arousal, attention, and emotion, but also to develop adaptive technologies that expand access to music-making opportunities and allow patients to extend their participation in these activities through periods of cognitive decline.
Tina Tallon, Ph.D. is an Assistant Professor of Artificial Intelligence and Music Composition; Area Coordinator of Composition at Ohio State University.