Truth: "State of the art LLMs don't accurately diagnose patients (performing worse than physicians), don't follow guidelines, cannot interpret lab results, fail to follow instructions, and are sensitive to both the quantity and order of information." nature.com/articles/s4159…
Rather than expect perfection from AI, we should assess how AI performs relative to humans, and, even better, how human+AI performs compared to humans alone.
Most of what we do has no proven downstream outcome effects. IMHO the main reasons the radiology AI companies have not met investor expectations are:
1. high quality clinical training data is a lot harder to come by than radiology AI startups anticipated.
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Hot off the press: We have developed a self-supervised learning method that is much better for pre-training than ImageNet--reduces labeling needs by an order of magnitude for medical imaging applications:
@StanfordAIMI@Radiology_AI
👋 Excited to share our latest work "Contrastive Learning of Medical Visual Representations from Paired Images and Text".
We propose a contrastive framework for learning visual representations of medical images from paired textual data.
arXiv: arxiv.org/abs/2010.00747
👇 (1/7)
Just got my hard copy of @jeremyphoward@GuggerSylvain book today & can’t wait to crack it. (I sat in on the @fastai course earlier this year, but a great way to review.)
And I am delighted to share the “blurb box” with the quintessential AI author @NorvigPeter@StanfordAIMI
I am heartbroken to say goodbye to one of the best individuals I have ever known. He was a brilliant man, not just about science but about people. A wonderful warm and caring person who truly loved those who worked for him and with him. May he rest in peace.
My attempt to provide scientific support for the case I have been making in various venues over the last couple of years that AI won’t replace radiologists:
Confirming what many believed about deep learning image reconstruction:
"Deep learning typically yields unstable methods for image reconstruction from: 1) tiny perturbations, 2) structural changes, and 3) changes in the number of samples." @Radiology_AIpnas.org/content/early/…
Are you a doc or other health worker who wants to get involved with AI? You may be asking:
--What do I need to learn?
--Where should I start?
--What online courses are available?
I looked into these questions during a recent sabbatical: towardsdatascience.com/getting-starte…@Radiology_AI