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Found 3 papers, 1 papers with code
Human Evaluation and Correlation with Automatic Metrics in Consultation Note Generation
In recent years, machine learning models have rapidly become better at generating clinical consultation notes; yet, there is little work on how to properly evaluate the generated consultation notes to understand the impact they may have on both the clinician using them and the patient's clinical safety.
Towards more patient friendly clinical notes through language models and ontologies
Our method based on a language model trained on medical forum data generates simpler sentences while preserving both grammar and the original meaning, surpassing the current state of the art.
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word Vectors
Recent literature suggests that averaged word vectors followed by simple post-processing outperform many deep learning methods on semantic textual similarity tasks.
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