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Found 4 papers, 2 papers with code
A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models
In this work, we investigate the potential of large language models to generate patient summaries based on doctors' notes and study the effect of training data on the faithfulness and quality of the generated summaries.
Machine Learning for Health symposium 2023 -- Findings track
A collection of the accepted Findings papers that were presented at the 3rd Machine Learning for Health symposium (ML4H 2023), which was held on December 10, 2023, in New Orleans, Louisiana, USA.
TabLLM: Few-shot Classification of Tabular Data with Large Language Models
We study the application of large language models to zero-shot and few-shot classification of tabular data.
Large Language Models are Few-Shot Clinical Information Extractors
A long-running goal of the clinical NLP community is the extraction of important variables trapped in clinical notes.
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