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Found 3 papers, 2 papers with code
Predicting postoperative risks using large language models
Adapting models through self-supervised finetuning further improved performance by 3. 2% for AUROC & 1. 5% for AUPRC Incorporating labels into the finetuning procedure further boosted performances, with semi-supervised finetuning improving by 1. 8% for AUROC & 2% for AUPRC & foundational modelling improving by 3. 6% for AUROC & 2. 6% for AUPRC compared to self-supervised finetuning.
Self-explaining Hierarchical Model for Intraoperative Time Series
Towards this end, we propose a hierarchical model combining the strength of both attention and recurrent models for intraoperative time series.
Surgical Prediction with Interpretable Latent Representation
Given the risks and cost of surgeries, there has been significant interest in exploiting predictive models to improve perioperative care.
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