Medical AI testing is unsafe, but addressing hidden stratification may be a way to prevent harm, without upending the current regulatory environment.
Improving Medical AI Safety by Addressing Hidden Stratification
Tag: medical data
Half a million x-rays! First impressions of the Stanford and MIT chest x-ray datasets
My first impressions of these datasets. How do they measure up, and how useful might they be?
The unreasonable usefulness of deep learning in medical image datasets
Medical data is horrible to work with, but deep learning can quickly and efficiently solve many of these problems.
Exploring the ChestXray14 dataset: problems
A couple of weeks ago, I mentioned I had some concerns about the ChestXray14 dataset. I said I would come back when I had more info, and since then I have been digging into the data. I've talked with Dr Summers via email a few times as well. Unfortunately, this exploration has only increased my concerns about the dataset.
Do machines actually beat doctors? ROC curves and performance metrics
Deep learning research in medicine is a bit like the Wild West at the moment; sometimes you find gold, sometimes a giant steampunk spider-bot causes a ruckus. This has derailed my series on whether AI will be replacing doctors soon, as I have felt the need to focus a bit more on how to assess … Continue reading Do machines actually beat doctors? ROC curves and performance metrics
Lauren Oakden-Rayner 