Phase NA RCT Launches: GPT-Assisted Multimodal Visual Language Model vs Conventional Evaluation for Acute Cardiopulmonary Presentations in the ED — What Clinicians Need to Know
247 Health News Editorial
·27 July 2026
·4 min read
·clinical-trialsThe ER-VISION-AI Study (NCT07727590) is a prospective, multicentre RCT evaluating whether GPT-assisted multimodal visual language model diagnostic support improves diagnostic concordance in 1,000 ED patients presenting with acute cardiopulmonary symptoms. Sponsored by Ewha Womans University Mokdong Hospital in South Korea, the trial integrates ECG, chest radiograph, and structured clinical data into a physician-supervised AI workflow, with results expected by end of 2028.
Originally reported by ClinicalTrials.gov
References
- 1.Ewha Womans University Mokdong Hospital. (2025). Multimodal visual language model-assisted diagnostic strategy in the emergency department: A prospective multicenter randomized controlled trial (ER-VISION-AI Study) [Clinical trial registration NCT07727590]. ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT07727590
- 2.Topol, E. J. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. https://doi.org/10.1038/s41591-018-0300-7
- 3.Storrow, A. B., & Gibler, W. B. (2000). Chest pain centers: Diagnosis of acute coronary syndromes. Annals of Emergency Medicine, 35(5), 449–461. https://doi.org/10.1067/mem.2000.105773
- 4.Hansson, L., Hedner, T., & Dahlöf, B. (1992). Prospective randomized open blinded end-point (PROBE) study: A novel design for intervention trials. Blood Pressure, 1(2), 113–119. https://doi.org/10.3109/08037059209077502
- 5.Newman-Toker, D. E., Schaffer, A. C., Yu-Moe, C. W., Nassery, N., Saber Tehrani, A. S., Clemens, G. D., Wang, Z., Zhu, Y., Fanai, M., & Siegal, D. (2019). Serious misdiagnosis-related harms in malpractice claims: The 'Big Three' — vascular events, infections, and cancers. Diagnosis, 6(3), 227–240. https://doi.org/10.1515/dx-2019-0019
- 6.Rajpurkar, P., Chen, E., Banerjee, O., & Topol, E. J. (2022). AI in health and medicine. Nature Medicine, 28(1), 31–38. https://doi.org/10.1038/s41591-021-01614-0
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247 Health News Editorial
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