Moving beyond the lines: lung ultrasound pixel-wise computer-assisted analysis for critically ill patients

[...]we prospectively recruited adult COVID-19 patients who were in ARF (defined by blood oxygen saturation as measured by pulse oximetry or = 30 breaths/min) at hospital admission (University Hospital of Toulouse and Cayenne Hospital, France, between July 2020 and March 2021). Furthermore, because the use of artificial intelligence methods for the development of computer-based aid to medical decision tools can be hindered by the poor explicability of the obtained results, we increased the explicability of our LUS data classifier, by using machine learning methods not as a black box, but as a pre-processing step to a signal analysis process that refine the result of the network. SEE PDF] We think that our work opens the door toward plausible improved diagnosis [1], automated severity scoring [2], medical triage [3], monitoring [4] and personalized treatment [5] for critically ill patients with acute respiratory failure.