The field of clinical NLP aims at applying NLP tools to clinical text, i.e. hospital records, clinican's notes, etc. Data from the clinical domain is notoriously difficult to process automatically due to large variation, sparse data and the large cost associated with the manual annotation of such data. A key challenge in the area of clinical NLP is the access to real, clinical data, due to strict ethical and privacy regulations.
AHUS is a large hospital in the Oslo region and this thesis will be a collaborative effort between LTG and the HØKH research center at AHUS. They have unique competence in all aspects of access and processing of clinical data and the master candidate will have a unique opportunity to work on real clinical data in a highly cross-disciplinary setting where the candidate will be given a work space at AHUS from which to conduct the project.
The precise details and scope of the thesis will be further decided in agreement between the supervisors and the candidate. The project presupposes a good balance of technical and linguistic expertise. Good programming skills, experience with machine learning and a solid background in NLP are relevant qualifications. Please contact the supervisors to discuss further details.