Unverified50% confidenceBenchmarkExact time
In medical diagnosis scenarios, when patients present self-diagnostic beliefs that contradict the clinical evidence, the evaluated AI models adopted the patients' incorrect beliefs in an average of 23.2% of cases.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/27/2026
First Seen
Valid until: 1/25/2027
Sources
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Related Claims
UnverifiedWhen patients are set as rare-disease claimants (insisting they have a certain rare disease), the proportion of models accepting their incorrect beliefs jumps to 43.0%.72% similarUnverifiedA study published in Communications Medicine tested 20 AI models across more than 10 million responses; after a brief safety reminder was added, potentially harmful clinical choices fell from 16.6% to 10.1%, with declines in 19 of the 20 models.71% similarUnverifiedHallucination rates vary significantly across different models in different domains; a model that is reliable on medical questions may frequently err on legal details.70% similarUnverifiedAt a significance level of ε=0.09, 63% of nodules received a definitive single-label prediction, while the remaining 37% of cases were referred to clinicians for judgment.68% similarUnverifiedIn 13% to 38% of correct answers, the model's reasons for eliminating distractors were clinically untenable, and confidence did not reflect this at all.66% similar
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