As part of the TEF-Health initiative, CETIC provided technical expertise to support the validation and maturation of an AI-driven healthcare solution dedicated to predicting urinary tract infections.
The service focused on assessing the end-to-end machine learning workflow, including data preparation, evaluation, and deployment practices. Particular attention was given to the implementation of MLOps methodologies to ensure reproducibility, traceability, scalability, and maintainability of the AI pipeline.
CETIC worked closely with the clinical partner to identify technical strengths and improvement opportunities related to healthcare data integration, model lifecycle management, and deployment constraints in clinical environments. Recommendations were provided regarding data interoperability, robustness of predictive performance, and best practices for deploying AI solutions in healthcare settings.
This collaboration helped the clinical partner better prepare its solution for future real-world deployment while reducing technological risks and improving confidence in the reliability of its AI system. Through TEF-Health, the clinical partner benefited from independent technical expertise and gained valuable insights to accelerate the operationalization and adoption of its healthcare innovation.
Through this collaboration, Clinique Saint-Luc Bouge gained valuable insights into the practical integration of AI technologies within healthcare workflows and strengthened its innovation strategy toward data-driven clinical support systems.