Much of Radiology and Pathology specimen interpretation is based on reliable and consistent detection. To come and think of it, the application of AI into this area is fantastic because it removes human fatigue and missed diagnoses. AI neural nets seem well equipped for image recognition. At the very least, this can lead to a first level flagging of specimens.
My only concern is that with any system, a major downside would be that human operators would place too much reliance on a system that works great most of the time, resulting in missing something that otherwise would have been caught. This happens every once in a while, such as with EKG machines spitting out a diagnosis based on electrical activity patterns.
My only concern is that with any system, a major downside would be that human operators would place too much reliance on a system that works great most of the time, resulting in missing something that otherwise would have been caught. This happens every once in a while, such as with EKG machines spitting out a diagnosis based on electrical activity patterns.