Fully autonomous medical AI is here, but are we treating it with the caution it deserves?
No Doctor Required: Autonomy, Anomalies, and Magic Puddings
Tag: medicine
It’s complicated. A deep dive into the Viz/Medicare AI reimbursement model.
CMS will reimburse an AI stroke detection model through Medicare/Medicaid. It is so darn complicated that it deserves a much deeper look.
The medical AI floodgates open, at a cost of $1000 per patient.
AI is finally getting paid, apparently at a rate of $1000 per patient. What?
Improving Medical AI Safety by Addressing Hidden Stratification
Medical AI testing is unsafe, but addressing hidden stratification may be a way to prevent harm, without upending the current regulatory environment.
The best medical AI research (that you probably haven’t heard of)
I discuss a piece of medical AI research that has not received much attention, but actually did a proper clinical trial!
Medical AI Safety: We have a problem.
For the first time ever AI systems can directly harm patients. Are we doing enough to prevent a medical AI tragedy, the equivalent of a thalidomide event?
Explain yourself, machine. Producing simple text descriptions for AI interpretability.
Humans explain their decisions with words. In our latest work, we suggest AI systems should do the same.
The philosophical argument for using ROC curves
I just wanted to do a quick follow up to my recent blog post, which discussed the performance metrics I think might be appropriate for use in medical AI studies. One thing I didn't cover was the reason we might want to use multiple metrics, or the philosophy behind choosing the ones I did. So today, … Continue reading The philosophical argument for using ROC curves
2017 in review: progress, problems, and predictions
2017 was cool. Medical AI progressed apace, the AI community grew up some and got a bit creative, and I made some predictions that mostly held up to vague scrutiny.
The End of Human Doctors – The Bleeding Edge of Medical AI Research (Part 3)
Today I want to look at two papers which tell us something very useful about medical AI, particularly if we are trying to predict the future of medicine.
Lauren Oakden-Rayner 