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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

Will Artificial Intelligence Translate Big Data Into Improved Medical Care or Be a Source of Confusing Intrusion? A Discussion Between a (Cautious) Physician Informatician and an (Optimistic) Medical Informatics Researcher

Will Artificial Intelligence Translate Big Data Into Improved Medical Care or Be a Source of Confusing Intrusion? A Discussion Between a (Cautious) Physician Informatician and an (Optimistic) Medical Informatics Researcher

Drs Nelson and Zeng-Treitler work together at the Biomedical Informatics Center at George Washington University. In the following we present a hypothetical dialogue which grew out of discussions they had as they considered their differing viewpoints of how artificial intelligence (AI) has developed and where it is going. While Dr Zeng-Treitler’s view of the future of AI is highly optimistic, Dr Nelson's opinion is more cautious.

Qing Zeng-Treitler, Stuart J Nelson

J Med Internet Res 2019;21(11):e16272

Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches

Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches

Among the 486 pictographs, only 29 had the exact same ratings, although the rating differences were fairly small ( As part of our analysis, the test pictographs were classified as direct, indirect, and arbitrary according to the representation strategies outlined by Nakamura and Zeng-Treitler [47]. Direct representation explored the visual similarity between a pictograph and its referent, (eg, depicting a thermometer directly).

Jinqiu Kuang, Lauren Argo, Greg Stoddard, Bruce E Bray, Qing Zeng-Treitler

J Med Internet Res 2015;17(12):e281

Computer-Assisted Update of a Consumer Health Vocabulary Through Mining of Social Network Data

Computer-Assisted Update of a Consumer Health Vocabulary Through Mining of Social Network Data

Examples of biomedical ATRs are Collier et al’s hidden Markov model for identifying gene names and gene products, as well as Frantzi et al’s “C-value” and Zeng et al’s “termhood” score [17-19]. Since C-value and termhood scores are used in our study, we will briefly describe them here. The C-value equation uses part of speech-tagged data and restricts candidate terms to noun phrases.

Kristina M M Doing-Harris, Qing Zeng-Treitler

J Med Internet Res 2011;13(2):e37