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Predicting rehabilitation curves with NLP-based extracted ICF functioning levels from clinical patient notes.

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorAbeln, Sanne
dc.contributor.authorFrinking, Stan
dc.date.accessioned2024-08-05T23:02:08Z
dc.date.available2024-08-05T23:02:08Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/47098
dc.description.abstractThis thesis describes how the inclusion of automatically extracted ICF functioning levels from in-patient clinical notes as features for post-discharge rehabilitation prediction can improve its performance.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectPredicting rehabilitation curves with NLP-based extracted ICF functioning levels from clinical patient notes.
dc.titlePredicting rehabilitation curves with NLP-based extracted ICF functioning levels from clinical patient notes.
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsNLP, rehabilitation, prediction, healthcare, ICF
dc.subject.courseuuArtificial Intelligence
dc.thesis.id35956


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