ER-VISION-AI Study

Prospective, multicenter, randomized, open-label, blinded-endpoint (PROBE-like) clinical trial evaluating whether physician-supervised Generative Pre-trained Transformer (GPT)-assisted multimodal diagnostic support improves diagnostic concordance in emergency department patients presenting with acute cardiopulmonary symptoms.

Inclusion Criteria: * Age ≥18 years * Presentation to a participating emergency department with acute cardiopulmonary symptoms, including chest pain, dyspnea, palpitations, syncope, dizziness, or fever accompanied by cardiopulmonary symptoms * Performance of both a standard 12-lead electrocardiogram and chest radiography during the initial emergency department evaluation * Availability of initial clinical assessment, vital signs, laboratory findings, and all mandatory clinical information required for the multimodal AI workflow * Expected emergency department observation or hospital admission for at least 24 hours * Ability and willingness to provide written informed consent Exclusion Criteria: * Inability or refusal to provide written informed consent * Requirement for immediate life-saving intervention that precludes completion of the study workflow * Death before completion of the initial emergency department diagnostic assessment * Electrocardiographic quality insufficient for reliable physician or Artificial intelligence (AI) interpretation * Chest radiographic quality insufficient for reliable physician or Artificial intelligence (AI) interpretation * Cardiac pacing rhythm * Missing mandatory clinical information required for the multimodal Artificial intelligence (AI) workflow * Previous enrollment in the ER-VISION-AI trial * Inability to establish a blinded adjudicated reference diagnosis