AI-assisted Rare Disease Diagnosis

A multicentre randomised controlled trial evaluating whether a rare-disease diagnostic large language model can improve diagnostic quality, efficiency, and health-economic outcomes for physicians managing patients with suspected rare or diagnostically unresolved disease.

Patient Inclusion Criteria: * Any age. Legal guardian co-signs consent for minors or individuals lacking legal capacity. * Diagnostically unresolved or suspected rare disease, with at least one prior complete clinical evaluation at a secondary-level or higher institution yielding no confirmed explanatory diagnosis. * First presentation to the enrolling institution for the current condition, with no prior records in the institutional HIS or outpatient system. * No prior genetic testing related to the current condition; no results or reports available. * Written informed consent provided voluntarily by patient or legal guardian, with commitment and ability to complete structured follow-up. Patient Exclusion Criteria: * Confirmed diagnosis (clinical, pathological, or molecular) explaining the primary symptoms. * Emergency presentation, critical illness, or any condition incompatible with trial participation. * Neither patient nor legally authorised proxy able to complete follow-up. * Concurrent enrollment in another interventional study with diagnostic accuracy or genetic testing yield as a primary endpoint. * Prior use of another AI system has already yielded a confirmed diagnosis for the current condition. Physician Inclusion Criteria * Licensed physician in internal medicine, neurology, pediatrics, general medicine, rare disease, or a related specialty. * ≥2 years of clinical practice; competent to manage rare disease patients; stratified into junior or senior tier. * Voluntary participation with written informed consent. Physician Exclusion Criteria * No longer in clinical practice, or unable to fulfill required outpatient duties during the study period. * Unwilling to provide informed consent or to permit protocol-required collection of consultation and questionnaire data. * Currently enrolled in another AI-assisted clinical workflow, or expected to be unable to comply with the procedures.