Classifying Implant-Bearing Patients via their Medical Histories: a Pre-Study on Swedish EMRs with Semi-Supervised GanBERT
Benjamin Danielsson, Marina Santini, Peter Lundberg, Yosef Al-Abasse, Arne Jonsson, Emma Eneling, Magnus Stridsman
Abstract
In this paper, we compare the performance of two BERT-based text classifiers whose task is to classify patients (more precisely, their medical histories) as having or not having implant(s) in their body. One classifier is a fully-supervised BERT classifier. The other one is a semi-supervised GAN-BERT classifier. Both models are compared against a fully-supervised SVM classifier. Since fully-supervised classification is expensive in terms of data annotation, with the experiments presented in this paper, we investigate whether we can achieve a competitive performance with a semi-supervised classifier based only on a small amount of annotated data. Results are promising and show that the semi-supervised classifier has a competitive performance with the fully-supervised classifier.- Anthology ID:
- 2022.lrec-1.581
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 5428–5435
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.581
- DOI:
- Cite (ACL):
- Benjamin Danielsson, Marina Santini, Peter Lundberg, Yosef Al-Abasse, Arne Jonsson, Emma Eneling, and Magnus Stridsman. 2022. Classifying Implant-Bearing Patients via their Medical Histories: a Pre-Study on Swedish EMRs with Semi-Supervised GanBERT. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 5428–5435, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Classifying Implant-Bearing Patients via their Medical Histories: a Pre-Study on Swedish EMRs with Semi-Supervised GanBERT (Danielsson et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.lrec-1.581.pdf