Computational Framework to Interpret Chest X-rays and Diagnose Pneumonia

It is estimated that 95% of the two million deaths due to pneumonia occur in developing countries. In Bangladesh alone, six million cases of pneumonia are diagnosed every year. Unfortunately, diagnostic methods to date lack sensitivity or are difficult to fully standardized. The lack of a reliable diagnostic hampers the execution of evidence based interventions, impacting the monitoring of interventions, like vaccines.

The “gold standard” for defining pneumonia are chest X-rays. However, the interpretations are subjective, sometimes requiring multiple radiologists/clinicians to reach a conclusive diagnosis. As there are few well-trained radiologists/clinicians in resource-poor settings, having a tool to aid in the diagnosis of pneumonia would be invaluable in the impact monitoring of interventions.

The aim of the project is to construct a computational framework to automatically and systematically interpret paediatric chest X-rays to diagnose pneumonia.

For further information, see: https://www.ed.ac.uk/usher/respire/acute-respiratory-disorders/interpret-chest-x-rays