Evaluating the Synergistic Impact of Fine-Tuning and Retrieval-Augmented Encoding on Enhancing Appendicitis Diagnosis from Limited HPI Notes

Abstract

This study explores the impact of fine-tuning combined with a retrieval-augmented encoding approach on encoder language model-generated embeddings for appendicitis diagnosis tasks using patients’ History of Present Illness notes, leading to significantly enhanced diagnostic performance.