Papers with medical examination tables

1 papers
EMGLLM: Data-to-Text Alignment for Electromyogram Diagnosis Generation with Medical Numerical Data Encoding (2025.findings-acl)

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Challenge: Existing Large Language Models struggle to interpret EMG tables . EMGLLM is a data-to-text model for medical examination tables based on electrical signals .
Approach: They propose a data-to-text model that aligns EMG data into word embeddings that reflect health degree.
Outcome: The proposed model outperforms baseline models in understanding EMG tables and generating high-quality diagnoses.

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