The reference for Chen et al. (2026) was erroneously cited in paragraph 9. The citation along with the reference “Chen, K.-Y., Chan, H.-C., Hwang, Y.-S., Lin, W.-W., and Chan, C.-M. (2026). Are Müller glial cells gatekeepers of neuroprotection and regeneration in age-related macular degeneration? Unraveling their roles in pathophysiology and therapeutic innovation. Prog. Retin. Eye Res. 112:101471. doi: 10.1016/j.preteyeres.2026.101471” will be removed.
A correction has been made to Paragraph 9. The paragraph will now read:
“The contributions collected in this Research Topic collectively indicate that the next phase of digital medicine should focus less on algorithmic novelty and more on generating clinically actionable evidence that supports routine healthcare implementation (Figure 1). Although the included studies demonstrate substantial advances across AI-enabled diagnostics, digital therapeutics, medical imaging, large language models, implementation science, and healthcare informatics, they also reveal several common priorities that should guide future research. Building upon these advances, future innovation is expected to further benefit from emerging technologies that complement the themes represented in this Research Topic, including mobile health (mHealth) (Wang et al., 2025), LLMs, generative artificial intelligence (Generative AI), wearable sensing systems (Song et al., 2026), federated learning (Fu et al., 2026), and multimodal foundation models (Wang et al., 2024b). However, their successful translation into clinical practice will depend not only on technological innovation but also on rigorous prospective validation, demonstrated clinical utility, seamless workflow integration, fairness, privacy-preserving learning, LLM safety, benchmark standardization, and appropriate regulatory oversight.”
The original version of this article has been updated.
Statements
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Summary
Keywords
artificial intelligence, digital medicine, explainable artificial intelligence (XAI), mobile healthcare, precision medicine
Citation
Wang MH, Lopes NP and Osório NS (2026) Correction: Editorial: Digital medicine and artificial intelligence. Front. Artif. Intell. 9:1965611. doi: 10.3389/frai.2026.1965611
Received
12 August 2026
Accepted
24 August 2026
Published
03 September 2026
Volume
9 - 2026
Edited and reviewed by
Thomas Hartung, Johns Hopkins University, United States
Updates
Copyright
© 2026 Wang, Lopes and Osório.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Mini Han Wang, 1155187855@link.cuhk.edu.hk
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.