Predicting postoperative risks using large language models

1 code implementation • 27 Feb 2024 • Bing Xue, Charles Alba, Joanna Abraham, Thomas Kannampallil, Chenyang Lu

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.

Domain Adaptation Multi-Task Learning +1