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| Publications [#371274] of Lawrence Carin
Papers Published
- Si, S; Wang, R; Wosik, J; Zhang, H; Dov, D; Wang, G; Henao, R; Carin, L, Students Need More Attention: BERT-based Attention Model for Small Data with Application to Automatic Patient Message Triage,
Proceedings of Machine Learning Research, vol. 126
(January, 2020),
pp. 436-456
(last updated on 2024/12/31)
Abstract: Small and imbalanced datasets commonly seen in healthcare represent a challenge when training classifiers based on deep learning models. So motivated, we propose a novel framework based on BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical TextMining). Specifically, (i) we introduce Label Embeddings for Self-Attention in each layer of BERT, which we call LESA-BERT, and (ii) by distilling LESA-BERT to smaller variants, we aim to reduce overfitting and model size when working on small datasets. As an application, our framework is utilized to build a model for patient portal message triage that classifies the urgency of a message into three categories: non-urgent, medium and urgent. Experiments demonstrate that our approach can outperform several strong baseline classifiers by a significant margin of 4.3% in terms of macro F1 score.
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