We plan to design a robust, reliable and trustworthy deep learning model to detect tuberculosis from chest X-ray images.
Our approach includes: i) implementing a benchmark model with context-aware features, ii) designing a framework for reliable uncertainty quantification of predictions, iii) investigating covariate shift in optimising training and testing datasets, and iv) conducting feasibility analysis for real-case deployment.