From the Journals
How AI Is Shaping Thyroid Disease Care
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By
February 5, 2026
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4 min
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1
AI's role in thyroid disease management has broadened over 3 decades.
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2
Systematic review evaluated AI applications in diagnostics and treatments.
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3
Major advances in imaging and pathology analysis reported.
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4
Challenges include the black-box nature of AI and workflow integration.
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5
Future research priorities highlighted for improving AI use in clinics.
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Artificial intelligence (AI) has significantly evolved in thyroid disease research, expanding from diagnosis to comprehensive management strategies over the past three decades. A systematic review highlights AI's advancements in image analysis, pathology, and personalized treatment. Despite impressive clinical applications, challenges remain, such as the black-box model of AI and integration into clinical workflows. Priorities for future research include cross-modal data usage and prospective trials to evaluate impact and enhance adoption in real-world settings. The study was led by Dr. Qing Lu from Huazhong University.
-
1
AI's role in thyroid disease management has broadened over 3 decades.
-
2
Systematic review evaluated AI applications in diagnostics and treatments.
-
3
Major advances in imaging and pathology analysis reported.
-
4
Challenges include the black-box nature of AI and workflow integration.
-
5
Future research priorities highlighted for improving AI use in clinics.
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