Machine Learning for Violence Risk Assessment Using Dutch Clinical Notes
- URL: http://arxiv.org/abs/2204.13535v1
- Date: Thu, 28 Apr 2022 14:36:06 GMT
- Title: Machine Learning for Violence Risk Assessment Using Dutch Clinical Notes
- Authors: Pablo Mosteiro and Emil Rijcken and Kalliopi Zervanou and Uzay Kaymak
and Floortje Scheepers and Marco Spruit
- Abstract summary: Violence risk assessment in psychiatric institutions enables interventions to avoid violence incidents.
We explore conventional and deep machine learning methods to assess violence risk in psychiatric patients using practitioner notes.
- Score: 0.988455728566886
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Violence risk assessment in psychiatric institutions enables interventions to
avoid violence incidents. Clinical notes written by practitioners and available
in electronic health records are valuable resources capturing unique
information, but are seldom used to their full potential. We explore
conventional and deep machine learning methods to assess violence risk in
psychiatric patients using practitioner notes. The performance of our best
models is comparable to the currently used questionnaire-based method, with an
area under the Receiver Operating Characteristic curve of approximately 0.8. We
find that the deep-learning model BERTje performs worse than conventional
machine learning methods. We also evaluate our data and our classifiers to
understand the performance of our models better. This is particularly important
for the applicability of evaluated classifiers to new data, and is also of
great interest to practitioners, due to the increased availability of new data
in electronic format.
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