aceCan AI assist in reducing diagnostic error? A narrative review
Diagnostic error, defined as missed, wrong, or delayed diagnoses or those not communicated to patients, is common, affecting 5-10 % of hospital admissions and clinic visits. Such errors cause patient harm in up to 1 in 100 of such encounters and account for 10 % of all hospital deaths and serious adverse events. About 80 % of diagnostic errors are potentially preventable, most resulting from flaws in clinician reasoning in formulating and testing diagnostic hypotheses. The advent of artificial intelligence (AI),…
AI and large language models have matured to improve clinicians' diagnostic decision-making during bedside and clinic consultations and help institutions increase diagnostic safety, addressing preventable diagnostic errors.
Rapid LLM iteration means diagnostic capabilities are not stable and require ongoing evaluation.
Evidence
- Peer-reviewedDiagnosis2026-07-22
How should this claim be treated?
Truvace Impact Record TRV-2026-0506, v1: “Can AI assist in reducing diagnostic error? A narrative review.” Truvace, 2026-07-22. /record/TRV-2026-0506 (accessed at citation time). sha256 f4807eb872bc9d25…
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