Chest radiography is one of the most ubiquitous medical imaging modalities. Nevertheless, the interpretation of chest radiography images is time-consuming and complex meaning that the field is ripe for a takeover from artificial intelligence systems. The high image throughput has allowed for the creation of large annotated datasets which have in turn been used to train deep learning systems that can obtain near-human performance. But are these systems ready for the clinic? In this presentation, the main challenges in the development and application of deep learning systems in chest radiography will be presented with a focus on interpretability and a case study on the COVID-19 pandemic.
Artificial Intelligence in Chest Radiography: Growing pains and Interpretability
May 30, 2023
1:00 pm