Revolutionising chest X-ray reporting: real-time automated triage and prioritisation of chest X-rays using an artificial intelligence system to improve diagnostic performance and outcomes
Prof Giovanni Montana
University of Warwick
Imaging underpins most medical decisions in healthcare systems, and chest radiography accounts for 40% of medical imaging worldwide. It is vital for swift diagnosis of life-threatening diseases and it can improve patient safety. However, many countries do not have the resources to use the technology.
We will develop and pilot existing AI-based software that has the potential to transform how chest radiographs are reported. The AI autonomously distinguishes normal from abnormal chest radiographs and can be used to triage patients. Its ability to accurately classify abnormal radiographs can be used to prioritise radiographs for expert reporting, where they can be classified as critical, urgent or non-urgent. This reduces time to diagnosis and allows better resource allocation.
The proposed technology will be integrated with existing picture archiving and communication systems and will be available as a mobile app. This will improve the time it takes to diagnose patients which will improve patient outcomes.