Integrating ChatGPT into Secure Hospital Networks: A Case Study on
  Improving Radiology Report Analysis
Kyungsu Kim Junhyun Park Saul Langarica Adham Mahmoud Alkhadrawi Synho Do
This study demonstrates the first in-hospital adaptation of a cloud-based AI,
similar to ChatGPT, into a secure model for analyzing radiology reports,
prioritizing patient data privacy. By employing a unique sentence-level
knowledge distillation method through contrastive learning, we achieve over 95%
accuracy in detecting anomalies. The model also accurately flags uncertainties
in its predictions, enhancing its reliability and interpretability for
physicians with certainty indicators. These advancements represent significant
progress in developing secure and efficient AI tools for healthcare, suggesting
a promising future for in-hospital AI applications with minimal supervision.