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Correction: Clinical Efficacy of Multimodal Exercise Telerehabilitation Based on AI for Chronic Nonspecific Low Back Pain: Randomized Controlled Trial

Correction: Clinical Efficacy of Multimodal Exercise Telerehabilitation Based on AI for Chronic Nonspecific Low Back Pain: Randomized Controlled Trial

In the Acknowledgements, the following sentence has been added: Jihua Zou, Qing Zeng, and Guozhi Huang are corresponding authors and contributed equally to this work. The correction will appear in the online version of the paper on the JMIR Publications website, together with the publication of this correction notice. Because this was made after submission to Pub Med, Pub Med Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.

Chongwu Xiao, Yijin Zhao, Gege Li, Zhuodong Zhang, Siyu Liu, Weichao Fan, Jinjing Hu, Qiuru Yao, Chengduan Yang, Jihua Zou, Qing Zeng, Guozhi Huang

JMIR Mhealth Uhealth 2025;13:e78188

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