By now, you’ve probably seen a few, if not many, articles on how deep learning could help detect COVID-19. In particular, convolutional neural networks (CNNs) have been studied as a faster and cheaper alternative to the gold-standard PCR test by just analyzing the patient’s computed tomography (CT) scan. It’s not surprising since CNN is excellent at image recognition; many places have CT scanners rather than COVID-19 testing kits (at least initially).

Despite its success in image recognition tasks such as the ImageNet challenge, can CNN really help doctors detect COVID-19? If it can, how accurately can it do so? It’s well known that CT scans are sensitive but not specific to COVID-19. That is, COVID-19 almost always produces abnormal lung patterns visible from CT scans. However, other pneumonia can create the same abnormal patterns. Can the powerful and sometimes magical CNN tackle this ambiguity issue?

#deep-learning #data-science #supervised-learning #machine-learning #covid19