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Posted: 2025-05-10 21:45:32 UTC
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
Status
Last Updated
2025-05-10 21:45:45 UTC
Verified By
Rollup News
A study of 444 deep learning models for head & neck medicine found that none were used in real-world clinics, with most being academic demos optimized for papers rather than patient care. The lack of real-world testing and adherence to reporting standards hinders the translation of AI tools into clinical practice.
Lack of real-world testing for AI models in medicine
Poor adherence to reporting standards (CONSORT, SPIRIT-AI)
Academic focus over patient-centered application
Incentives needed for real-world AI testing
Lack of external validation
Poor model explainability
Failure to meet reporting standards
Focus on academic demos instead of clinical applications