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Predicting 30-Day Postoperative Mortality and American Society of Anesthesiologists Physical Status Using Retrieval-Augmented Large Language Models: Development and Validation Study

Predicting 30-Day Postoperative Mortality and American Society of Anesthesiologists Physical Status Using Retrieval-Augmented Large Language Models: Development and Validation Study

When compared to prior deep learning–based approaches, our method significantly outperforms the BERT–deep neural network (DNN) model of Chen et al [43] in mortality prediction. Specifically, our LLM with RAG integration achieved a substantially higher macro F1-score (0.7222, 95% CI 0.6998-0.7446) compared to their model (0.307, 95% CI 0.269-0.342), indicating a superior balance between precision and recall across both mortality and survival classes.

Ying-Hao Chen, Shanq-Jang Ruan, Pei-fu Chen

J Med Internet Res 2025;27:e75052

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