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

Quick thoughts on ChestXray14, performance claims, and clinical tasks.

So, the big news in medical AI research is that the Stanford ML group under Andrew Ng has released a paper on chest x-ray interpretation that claims human performance at identifying pneumonia. First up, very cool! Second up, I have concerns. Vague and not so vague discomforts. So, after having a few days to wrap … Continue reading Quick thoughts on ChestXray14, performance claims, and clinical tasks.

The End of Human Doctors – The Bleeding Edge of Medical AI Research (Part 2)

Today we continue looking at breakthrough medical deep learning research, and review a major paper from Stanford researchers that reports "dermatologist level classification of skin cancer", published in Janurary 2017. As a reminder, a major focus of this dive into the state of the art research will be barriers to medical AI, particularly technical barriers. This … Continue reading The End of Human Doctors – The Bleeding Edge of Medical AI Research (Part 2)

The End of Human Doctors – The Bleeding Edge of Medical AI Research (Part 1)

More than any other part of this blog series, what we talk about today will have the most impact on whether machines are going to replace doctors anytime soon. We are going to start exploring the cutting edge of research in medical automation. In the previous articles in this series, we simply assumed deep learning can automate medical tasks. … Continue reading The End of Human Doctors – The Bleeding Edge of Medical AI Research (Part 1)