Show simple item record

Using LLMs to extract diagnoses from clinical texts in psychiatry

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorSiebes, Arno
dc.contributor.authorHoek, Marit
dc.date.accessioned2024-08-07T23:06:07Z
dc.date.available2024-08-07T23:06:07Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/47142
dc.description.abstractA pre-trained Transformer was inplemented wirh the aim of optimizing the extraction of diagnosis classifications from Dutch psychiatric texts. Within this process, the following attributes were compared: data used for pre-training, the classification method and oversampling.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectUsing LLMs to extract diagnoses from clinical texts in psychiatry
dc.titleUsing LLMs to extract diagnoses from clinical texts in psychiatry
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsTransformer; Large Language Model; Psychiatry; Diagnosis Classification
dc.subject.courseuuApplied Data Science
dc.thesis.id36204


Files in this item

Thumbnail
Name:
master_thesis_ADS_Marit_Hoek.pdf
Size:
729.7Kb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record