AI’s see things in medical images that humans cannot

Eric Topol:

We should have known a few years back that something was rich (dare I say eye-opening) about the retina that humans, including retinal experts, couldn’t see. While there are far simpler ways to determine gender, it’s a 50-50 toss up for ophthalmologists, which means there are no visible cues to human eyes. But now two models have shown 97% accuracy of gender determination from neural network training. That was just the beginning.

The amazing power of “machine eyes”

Machine learning models, and particularly neural networks, are going to glean details from medical images that are surprising and perhaps life saving.

But we still don’t know what they miss, and how reliable they are. Pairing them with human experts will be critical.