Machine learning vs. rule-based methods for document classification of electronic health records within mental health care—A systematic literature review
Natural Language Processing Journal, vol. 10, pp. 100129
Abstract
Document classification is a widely used task for analyzing mental healthcare texts. This systematic literature review focuses on the document classification of electronic health records in mental healthcare. Over the last decade, there has been a shift from rule-based to machine-learning methods. Despite this shift, no systematic comparison of these two approaches exists for mental healthcare applications. This review examines the evolution, applications, and performance of these methods over time. We find that for most of the last decade, rule-based methods have outperformed machine-learning approaches. However, with the development of more advanced machine-learning techniques, performance has improved. In particular, Transformer-based models enable machine learning approaches to outperform rule-based methods for the first time.
Authors 6
-
Emil Rijcken corresponding
Utrecht University · Eindhoven University of Technology
Affiliation as printed
Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, Utrecht, 3584 CC, The Netherlands
Jheronimus Academy of Data Science, Eindhoven University of Technology, Sint Janssingel 92, ’s-Hertogenbosch, 5211 DA, The Netherlands
-
Affiliation as printed
Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, Utrecht, 3584 CC, The Netherlands
-
Affiliation as printed
Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, Utrecht, 3584 CC, The Netherlands
Department of Methodology and Statistics, Utrecht University, Padualaan 14, Utrecht, 3584CH, The Netherlands
-
University Medical Center Utrecht
Affiliation as printed
Psychiatry, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CS, The Netherlands
-
Marco René Spruit Aachen Leiden Institute of Advanced Computer Science Public Health and Primary Care
Leiden University · Leiden University Medical Center
Affiliation as printed
Leiden Institute of Advanced Computer Science, Niels Bohrweg 1, Leiden, 2333 CA, The Netherlands
Public Health & Primary Care, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands
-
Eindhoven University of Technology
Affiliation as printed
Jheronimus Academy of Data Science, Eindhoven University of Technology, Sint Janssingel 92, ’s-Hertogenbosch, 5211 DA, The Netherlands
Cited by 16 stored of 17
16 results
No patents citing this paper on Lens.org (checked 2026-10-11).
References 122
-
W6631881933details pending0citations
-
W6725068802details pending0citations
-
W6726308897details pending0citations
-
W6740908302details pending0citations
-
W6754654208details pending0citations
-
W6754806280details pending0citations
-
W6754884518details pending0citations
-
W6769062845details pending0citations
-
W6782881760details pending0citations
-
W6790768727details pending0citations
-
W6792391489details pending0citations
-
W6794314438details pending0citations
-
W6806699330details pending0citations
-
W6807013993details pending0citations
-
W6810041718details pending0citations
-
W6810464144details pending0citations
-
W6831576529details pending0citations
-
W6842967054details pending0citations
-
W6847092842details pending0citations
-
W6849797818details pending0citations