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Ah, you're right. Something else I'm curious about with these systems is how they'll affect difficulty level. If AI handles the majority of easy cases, and radiologists are already at capacity, so they crack if the only cases they evaluate are now moderately to extraordinarily difficult?

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The problem is, you don't know beforehand if it's a hard case or not.

A hard to spot tumor is an easy negative result with high confidence by an AI

Let's look at mammography, since that is one of the easier imaging exams to evaluate. Studies have shown that AI can successfully identify more than 50% of cases as "normal" that do not require a human to view the case. If group started using that, the number of interpreted cases would drop in half although twice as many would be normal. Generalizing to CT of the abdomen and pelvis and other studies, assuming AI can identify a sub population of normal scans that do not have to be seen by a radiologist, the volume of work will decline. However, the percentage of complicated cases will go up. Easy, normal cases will not be supplementing the Radiologist income the way it has in the past. Of course, all this depends upon who owns the AI identifying normal studies. Certainly, hospitals or even packs companies would love to own that and generate that income from interpreting the normal studies. AI software has been slow to be adopted, largely because cases still have to be seen by a radiologist, and the malpractice issue has not been resolved. Expect rapid changes in the field once malpractice solutions exist.

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