It sounds to me like you are arguing that humans can’t improve machine learning models by studying them. That seems to be far from our reality. Most successful machine learning models we have today get tuned by humans for the task they are doing.
Why is not all the data for tackling this issue publicly available ?
Because people value privacy and don’t want their medical data being public.
The single model that was tried on this dataset claims to perform about as well as a radiologist. But imagine if we didn’t have only 1.2 million images, imagine if we had over 100 million and image if we didn’t have a single model, imagine if we had hundreds of them,
If the trainings dataset happens to be about how the average radialogist rates an image you don’t get better then a radiologist by looking at more images with the same labeling.
if we didn’t have a single team but rather hundreds of teams working on this problem.
If you look at Go as a casestudy, the progress when hundreds of teams were working at the problem was relatively slow. The progress took of when the single well-funded team at DeepMind spend it’s resources on the problem.
A few well-funded teams will likely do a better job at analysing cancer images and produce a commerical product then academic teams.
It sounds to me like you are arguing that humans can’t improve machine learning models by studying them. That seems to be far from our reality. Most successful machine learning models we have today get tuned by humans for the task they are doing.
Because people value privacy and don’t want their medical data being public.
If the trainings dataset happens to be about how the average radialogist rates an image you don’t get better then a radiologist by looking at more images with the same labeling.
If you look at Go as a casestudy, the progress when hundreds of teams were working at the problem was relatively slow. The progress took of when the single well-funded team at DeepMind spend it’s resources on the problem.
A few well-funded teams will likely do a better job at analysing cancer images and produce a commerical product then academic teams.