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Found 4 papers, 2 papers with code
Evaluation of General Large Language Models in Contextually Assessing Semantic Concepts Extracted from Adult Critical Care Electronic Health Record Notes
Methods: We investigated the performance of three general LLMs in understanding and processing real-world clinical notes.
Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact
Our weakly supervised models perform competitively with traditional supervised techniques and require less involvement from domain experts, demonstrating their use as efficient and practical alternatives to supervised learning in HC applications of ML.
Deep Normed Embeddings for Patient Representation
We introduce a novel contrastive representation learning objective and a training scheme for clinical time series.
Unifying Cardiovascular Modelling with Deep Reinforcement Learning for Uncertainty Aware Control of Sepsis Treatment
Sepsis is a potentially life threatening inflammatory response to infection or severe tissue damage.
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