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Classifying Implant...
Classifying Implant-Bearing Patients via their Medical Histories : a Pre-Study on Swedish EMRs with Semi-Supervised GAN-BERT
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- Danielsson, Benjamin (författare)
- Linköping University, Sweden
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- Santini, Marina, 1960- (författare)
- RISE,Prototypande samhälle
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- Lundberg, Peter (författare)
- Linköping University, Sweden
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visa fler...
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- Al-Abasse, Yosef (författare)
- Linköping University, Sweden
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- Jönsson, Arne (författare)
- Linköping University, Sweden
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- Eneling, Emma (författare)
- Linköping University, Sweden
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- Stridsman, Magnus (författare)
- Linköping University, Sweden
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visa färre...
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(creator_code:org_t)
- European Language Resources Association (ELRA), 2022
- 2022
- Engelska.
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Ingår i: 2022 Language Resources and Evaluation Conference, LREC 2022. - : European Language Resources Association (ELRA). - 9791095546726 ; , s. 5428-5435
- Relaterad länk:
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https://urn.kb.se/re...
Abstract
Ämnesord
Stäng
- 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 when compared with the fully-supervised classifier. © licensed under CC-BY-NC-4.0.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Language Technology (hsv//eng)
Nyckelord
- BERT
- clinical text mining
- electronic medical records
- EMR
- GAN-BERT
- text classification
- Classification (of information)
- Data mining
- Medical computing
- Text processing
- Electronic medical record
- Medical record
- Semi-supervised
- Supervised classifiers
- Text-mining
- Support vector machines
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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