91–94 of 94 posts
Earlier quoted context omitted.
It's been proven that using humans as ground truth you can ultimately build a NN off that data which outperforms the humans.
What is meant by proven? What is meant by "the humans"? And how can any human say that is so?
I do research in computer vision and this paper is so bad it's beyond words. * They give the network is huge advantage: they teach it that it should say "no" 80% of the time. The training data is unbalanced (80% no vs 20% yes) as is the test data. Of course it does well! I don't care what they do at training time, but the test data should be balanced or they should correct for this in the analysis. * They measure the…
Your first two suggestions combined together are very wrong. If you made the test dataset balanced and then measured PR curve the precision would be way too optimistic as it is directly affected by the class imbalance. ROC curve on the other hand is invariant to the test set imbalance.
You can find interesting this short article I have written about this problem: https://arxiv.org/abs/1812.01388
I do research in computer vision and this paper is so bad it's beyond words. * They give the network is huge advantage: they teach it that it should say "no" 80% of the time. The training data is unbalanced (80% no vs 20% yes) as is the test data. Of course it does well! I don't care what they do at training time, but the test data should be balanced or they should correct for this in the analysis. * They measure the…
But sensitivity and recall are the same thing...
I've always thought that diagnostic-oriented specialties would be most at risk (pathology, dermatology, radiology, ophthalmology). As long as you have procedures, you will have a need for an extremely competent clinician that can synthesize all information and coordinate with use of hands or devices.
All the specialties you cite entail various manual procedures. Other than that yes, robots are not capable of replacing manual work in médicine yet.