South Korean medical AI company Lunit’s chest X-ray analysis software demonstrated significant speed advantages over human radiologists in emergency room settings, according to a new study published in the European Journal of Radiology.
The research, conducted at Singapore’s Changi General Hospital, analyzed nearly 21,000 chest X-rays using Lunit’s AI solution. The system processed emergency cases in just 0.2 seconds, compared to 1.7 seconds for doctors, representing a 77% reduction in analysis time.
The technology showed particular strength in identifying urgent cases, achieving 99% specificity in emergency classifications. For routine X-rays, the system maintained accuracy rates above 89% across normal and non-emergency categories.
While the results suggest AI could help streamline hospital workflows, the study focused solely on X-ray classification rather than full diagnostic capabilities. The research team noted the technology could assist doctors in rapid decision-making for emergency patients.
Lunit CEO Seo Beom-seok claimed the findings validate the software’s real-world medical applications. The company did not disclose pricing or implementation costs for hospitals considering the technology.
The research adds to growing evidence of AI’s potential role in healthcare triage, though questions remain about integration challenges and long-term impact on medical staffing needs.
