Clinical staff outperform ChatGPT AI at emergency department triage, but AI shows promise as a support tool for urgent cases.
Key Details
- 1Study compared six doctors, 44 nurses, and ChatGPT 3.5 on triaging 110 clinical cases using the Manchester Triage System.
- 2Doctors achieved 70.6% accuracy, nurses 65.5%, and AI 50.4%; AI had lower sensitivity for urgent cases (58.3% vs. nurses 73.8%, doctors 83%).
- 3AI outperformed nurses in the most urgent triage category for accuracy (27.3% vs. 9.3%) and specificity (27.8% vs. 8.3%).
- 4AI tended to over-triage, assigning higher urgency more often than staff.
- 5Authors advocate for AI as an adjunct to, not replacement for, clinical judgement.
- 6Study limitations include small sample size, single center, and non-real-world AI setting.
Why It Matters
These findings emphasize the current limitations of general AI models in patient triage compared to clinical professionals, highlighting the need for cautious integration, oversight, and further development before AI can play a leading role in acute medical decision-making.
Source
EurekAlert
Related News
•EurekAlert
MD Anderson Unveils New AI Genomics Insights and Therapeutic Advances
MD Anderson reports breakthroughs in cancer therapeutics and provides critical insights into AI models for genomic analysis.
•EurekAlert
SH17 Dataset Boosts AI Detection of PPE for Worker Safety
University of Windsor researchers released SH17, a 8,099-image open dataset for AI-driven detection of personal protective equipment (PPE) in manufacturing settings.
•EurekAlert
AI Powers Breakthroughs in Optical Metasurface Design for Imaging
A review highlights how AI is revolutionizing the design of optical metasurfaces, advancing compact optics and computational imaging.