Clinical XLNet: Modeling Sequential Clinical Notes and Predicting Prolonged Mechanical Ventilation
arXiv:1912.11975
Abstract
Clinical notes contain rich data, which is unexploited in predictive modeling compared to structured data. In this work, we developed a new text representation Clinical XLNet for clinical notes which also leverages the temporal information of the sequence of the notes. We evaluated our models on prolonged mechanical ventilation prediction problem and our experiments demonstrated that Clinical XLNet outperforms the best baselines consistently.
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Cited by in corpus (5)
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- Interpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance
- Patient Cohort Retrieval using Transformer Language Models