https://www.sciencedaily.com/releases/2020/06/200624120434.htm

In recent years, artificial intelligence has been on the rise in the diagnosis of medical imaging. A doctor can look at an X-ray or biopsy to identify abnormalities, but this can increasingly also be done by an AI system by means of "deep learning" (see 'Background: what is deep learning' below). Such a system learns to arrive at a diagnosis on its own, and in some cases it does this just as well or better than experienced doctors.

The two major differences compared to a human doctor are, first, that AI is often not transparent in how it's analyzing the images, and, second, that these systems are quite "lazy." AI looks at what is needed for a particular diagnosis, and then stops. This means that a scan does not always identify all abnormalities, even if the diagnosis is correct. A doctor, especially when considering the treatment plan, looks at the big picture: what do I see? Which anomalies should be removed or treated during surgery?