avvakum

It does not matter whether the data is balanced or not when you report ROC (AUC), sensitivity and specificity for the purpose of comparison of two ways of image interpretation (e.g. humans vs. machines) as long as the evaluation is done on the same dataset with the same methodology. Obviously, the absolute numbers would not mean much outside of the study.

they fixed the dropdown for quota request

Same problem here and it does not seem to be zone specific. I wonder how others worked around this ...

Liability is of a radiologist is ultimately offset by malpractice insurance. Similarly, the lawyers would go for ML algorithm developers. Now I can see ML insurance business with premiums tied to ML clinical performance ... Obviously there has to be a legislation in place for this.

SharpMask looks very similar to a year-old "U-Net" http://arxiv.org/pdf/1505.04597