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Found 5 papers, 1 papers with code
Guided Discrete Diffusion for Electronic Health Record Generation
Electronic health records (EHRs) are a pivotal data source that enables numerous applications in computational medicine, e. g., disease progression prediction, clinical trial design, and health economics and outcomes research.
XAIQA: Explainer-Based Data Augmentation for Extractive Question Answering
Our method uses the idea of a classification model explainer to generate questions and answers about medical concepts corresponding to medical codes.
Surpassing GPT-4 Medical Coding with a Two-Stage Approach
Recent advances in large language models (LLMs) show potential for clinical applications, such as clinical decision support and trial recommendations.
Extend and Explain: Interpreting Very Long Language Models
While Transformer language models (LMs) are state-of-the-art for information extraction, long text introduces computational challenges requiring suboptimal preprocessing steps or alternative model architectures.
ReFACTor: Practical Low-Rank Matrix Estimation Under Column-Sparsity
Various problems in data analysis and statistical genetics call for recovery of a column-sparse, low-rank matrix from noisy observations.
