  Despite the rapid development of AI models in medical image analysis, their
validation in real-world clinical settings remains limited. To address this, we
introduce a generic framework designed for deploying image-based AI models in
such settings. Using this framework, we deployed a trained model for fetal
ultrasound standard plane detection, and evaluated it in real-time sessions
with both novice and expert users. Feedback from these sessions revealed that
while the model offers potential benefits to medical practitioners, the need
for navigational guidance was identified as a key area for improvement. These
findings underscore the importance of early deployment of AI models in
real-world settings, leading to insights that can guide the refinement of the
model and system based on actual user feedback.
