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Channel: automation – Luke Oakden-Rayner
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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...

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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...

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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.

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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.

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Medical AI Safety: Doing it wrong.

Medical AI has a safety problem; we know for a fact our testing isn't reliable. We've seen how this plays out before.

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