He ZX, Wang J, Yang JS. Expanding the applications of artificial intelligence in emergency radiology: Advancing precision medicine and resource efficiency. World J Radiol 2026; 18(1): 117814 [PMID: 41640709 DOI: 10.4329/wjr.v18.i1.117814]
Reader's ID:
05418651
Submitted on:
February 05, 2026, 21:57
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Reader Comments:
This Editorial thoroughly explores the field of AI use in diagnostic radiology.
It provides a complete overview of the potential and the current applications of AI in the field with great potential, strong diagnostic performance but in my opinion it does spotlight with the due consideration the potential drawbacks coming from the extensive use of AI in the clinical field.
The enthusiasm generated from the high precision and performance and the consequent advantages in terms of resource and time save for operators outpaced evaluation of broader consequences. Concerns include trainee deskilling, automation bias, unclear medicolegal accountability, and inequitable access due to infrastructure demands. The authors emphasize that technical accuracy alone is insufficient and call for longitudinal studies, training models that preserve independent reasoning, and deployment strategies that address equity. Without systematic assessment of professional, clinical, and societal impacts, AI adoption risks being driven by non-evidence-based factors.