REVIEW article
Front. Artif. Intell.
Sec. Medicine and Public Health
This article is part of the Research TopicArtificial Intelligence and Medical Image ProcessingView all 11 articles
AI-Navigated Shoulder Injection: Precision, Real-Time Learning and Clinical Translation
Provisionally accepted
- Third Hospital of Hebei Medical University, Shijiazhuang, China
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This review focuses on artificial intelligence (AI)-guided ultrasound-guided shoulder joint injections. We systematically retrieved relevant studies from PubMed, Embase, Cochrane Library, IEEE Xplore, and Web of Science (1996 ~ 2025). Literature was screened based on predefined inclusion/exclusion criteria, and evaluated AI technologies using core metrics including anatomical segmentation accuracy (Dice similarity coefficient), first-pass puncture success rate, and clinical outcome indicators (Visual analogue scale scores, VAS; American Shoulder and Elbow Surgeons, ASES scores). It explores the technical principles of AI medical image processing (segmentation, detection, tracking, reconstruction) and deep learning algorithms for shoulder anatomy, addressing limitations of traditional ultrasound guidance through AI-enabled precision targeting and real-time learning. Clinical applications, technological advancements, ethical controversies, and regulatory pathways are summarized. Key findings confirm AI enhances injection accuracy, first-pass success rates, and patient outcomes. This work provides a concise, evidence-based reference for clinicians and researchers, highlighting the paradigm shift of AI in optimizing shoulder injection therapy.
Keywords: AI-navigated navigation technology, artificial intelligence, regulation, Shoulder joint injection, Ultrasound guidance
Received: 05 Nov 2025; Accepted: 16 Feb 2026.
Copyright: © 2026 Li, Huang, Zhao and Cheng. 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) or licensor 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: Xiaodan Huang
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.