Cost-Effectiveness of AI in Ultrasound Image Quality Control
Study Overview
This study compared the cost-effectiveness of AI-based methods versus manual methods for ultrasound image quality control (QC) in perinatal screening.
Methods
Ultrasonographers and pregnant volunteers were recruited from Hunan Maternal and Child Health Hospital in May 2023. They were divided into two groups: one using AI for QC and the other using manual QC. Scores were recorded monthly to assess effectiveness.
Key Findings
- 14 ultrasonographers participated, with no significant differences in demographics between the two groups.
- The AI QC method showed better performance than manual QC, particularly in August, September, and October.
- AI QC scores improved over time, while manual QC scores did not show improvement.
- Time costs for AI QC were significantly lower, with real-time AI QC taking zero seconds compared to manual QC, which took over 20 minutes.
Conclusions
The AI QC method is more cost-effective and has the potential to improve skills in perinatal ultrasound screening, unlike the manual method, which only maintains current skill levels.
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