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Predicting Recovery of Persistent Symptoms After Sport-Related Concussions Using Machine Learning

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorStoep, Nathan van der
dc.contributor.authorImhof, Lisa
dc.date.accessioned2024-04-08T23:02:32Z
dc.date.available2024-04-08T23:02:32Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/46272
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectPrediction of high or low recovery in patients with persistent symptoms after a sport-related concussion. I used machine learning to classify patients into the high or low recovery group based on a subset of pre- (e.g. sex, age) and post-injury (e.g. self-reported symptoms, neurocognitive functioning) predictors.
dc.titlePredicting Recovery of Persistent Symptoms After Sport-Related Concussions Using Machine Learning
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuNeuroscience and Cognition
dc.thesis.id29863


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