ReviewFrontiers in endocrinology2026
Transforming thyroid disease education: AI and virtual technologies in residency training.
Review in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Thyroid cancer is the most common endocrine malignancy, and standardized residency training is critical for cultivating competent thyroid specialists. However, traditional training faces limitations including insufficient standardized clinical exposure, patient safety concerns, and inconsistent skill assessment. This narrative review analyzes the applications, benefits, challenges, and future directions of artificial intelligence (AI) and virtual reality (VR) in thyroid disease-focused residency training. A literature search was conducted across PubMed, Scopus, and Web of Science, identifying 42 eligible English and Chinese studies published between 2015 and 2025. Results show that AI-driven systems enable objective, real-time assessment of thyroid ultrasound skills, enhance diagnostic decision-making for thyroid nodules, and support adaptive personalized learning. VR simulation platforms provide immersive, risk-free environments for repetitive practice of thyroid surgeries (e.g., thyroidectomy), with AI analytics further enabling precise skill evaluation and longitudinal progress tracking. Despite these advantages, significant obstacles persist: ethical and data security risks, technical limitations in anatomical fidelity and haptic feedback, professional acceptance and curricular integration issues, high economic costs, and potential weakening of humanistic competence. Future development should adhere to a "human-centered, technology-assisted" principle, focusing on core technological breakthroughs, standardized evaluation system construction, phased curriculum integration, and governance mechanism improvement. This review concludes that AI and VR are valuable adjuncts to traditional residency training, with the ultimate goal of cultivating thyroid specialists with both solid clinical skills and humanistic care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.