Applied and Computational Engineering
- The Open Access Proceedings Series for Conferences
Proceedings of the 4th International Conference on Computing and Data Science (CONF-CDS 2022)
Series Vol. 2 , 22 March 2023
Open
Access | Article
Prediction of Skin Cancer Using Pre-Trained Language Models from Patient Symptoms
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Abstract
Automatic feature extraction and processing of greater data is now possible because of advances in Deep Learning. To pre-train from a wider corpus and comprehend the language feature for sentiment classification work, transformers Generalized Autoregressive Pre-training for Language Understanding and Bidirectional Encoder Representations from Transformers (BERT) have been proposed. These language models learn the context in both ways. In the proposed work, we have examined and tested our text dataset of skin cancer cases using the BERTbase model. When determining whether a patient's symptoms are compatible with cancer or not the model has a 97.3 percent accuracy rate.
Keywords
Bidirectional, Sentiment Classification, Transformers, Reviews, Encoders
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 4th International Conference on Computing and Data Science (CONF-CDS 2022)
- ISBN (Print)
- 978-1-915371-19-5
- ISBN (Online)
- 978-1-915371-20-1
- Published Date
- 22 March 2023
- Series
- Applied and Computational Engineering
- ISSN (Print)
- 2755-2721
- ISSN (Online)
- 2755-273X
- DOI
- 10.54254/2755-2721/2/20220626
- Copyright
- 22 March 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited