ChatGPT-4o with faculty guidance outperforms AI-only and traditional learning in ultrasonography training: a...

Ultrasonography training for residents is challenging owing to its operator-dependent nature and difficulties in mastering subtle image interpretation. Multimodal large language models like ChatGPT-4o enable efficient knowledge retrieval but show marked limitations in static ultrasonography image analysis.

In this prospective, single-centre randomized controlled trial, 45 first-year ultrasonography residents were randomly allocated to control (traditional resources), AI-only (ChatGPT-4o exclusively), or blended (ChatGPT-4o plus weekly faculty tutorials) groups. After a 3-week intervention, performance was assessed using a 150-item examination (pure-text and image-based multiple-choice questions). The study was approved by the institutional ethics committee, and written informed consent was obtained.

The blended group achieved the highest scores (mean 128.40 ± 18.25) vs. AI-only (119.87 ± 19.11) and control (110.60 ± 20.45; P = 0.02), with superior pure-text performance (P = 0.03) and significant advantages in obstetrics/gynaecology (P = 0.04) and superficial organ ultrasonography (P = 0.047). Examination time was shortest in the blended group (P = 0.03). ChatGPT-4o alone was 85% accurate on text but only 47% on image-based questions.

A faculty-guided AI-integrated strategy was associated with improved short-term post-intervention performance compared with AI-only or traditional learning; however, effects reflect the combined intervention and AI support for static ultrasound image interpretation remains limited.