CMS will reimburse an AI stroke detection model through Medicare/Medicaid. It is so darn complicated that it deserves a much deeper look.
It’s complicated. A deep dive into the Viz/Medicare AI reimbursement model.
Tag: deep learning
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?
The FDA has approved AI-based PET/MRI “denoising”. How safe is this technology?
Super-resolution promises to be one of the most impactful medical imaging AI technologies, but only if it is safe.
This week we saw the FDA approve the first MRI super-resolution product, from the same company that received approval for a similar PET product last year. This news seems as good a reason as any to talk about the safety concerns myself and many other people have with these systems.
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.
Ten controversial opinions about medical AI
Forget about interpretability, don't share your code or data, and remember, AI is magic.
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.
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.
Predicting Medical AI in 2017
Welcome to 2017! What a blast 2016 was. It seemed like every day there was a new, massive breakthrough in deep learning research. It was also the year that the wider world really started to take notice. The media, professional groups, and the general public all climbed aboard the AI hype train in 2016. Governments commissioned … Continue reading Predicting Medical AI in 2017
The three phases of medical AI trials
In a recent blogpost I explored how to critically read medical artificial intelligence research, focusing on the relevance of these experiments to clinical practice. It has since struck me that we don't have a simple, clear way to discuss the idea that some studies are still a still a long way off use in the clinics, and others … Continue reading The three phases of medical AI trials
Lauren Oakden-Rayner 