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Found 3 papers, 2 papers with code
Event-Based Contrastive Learning for Medical Time Series
In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event.
A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series
In this work, we use knowledge distillation via constrained variational inference to distill the knowledge of a powerful "teacher" neural network model with high predictive power to train a "student" latent variable model to learn interpretable hidden state representations to achieve high predictive performance for sepsis outcome prediction.
What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community.
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