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Everyone swooning with optimism over this result should the machine learning reddit comments on it first. https://old.reddit.com/r/MachineLearning/comments/ehp

Everyone swooning with optimism over this result should the machine learning reddit comments on it first. https://old.reddit.com/r/MachineLearning/comments/ehpllt/deep_learning_model_for_breast_cancer_detection/ https://old.reddit.com/r/MachineLearning/comments/ehpllt/dee... And also linked blog[edit]: https://lukeoakdenrayner.wordpress.com/2017/12/06/do-machines-actually-beat-doctors-roc-curves-and-performance-metrics/ https://lukeoakdenrayner.wordpress.com/2017/12/06/do-machine... TL;DR; There are sooo many subtlties to stuff like this that this things really shouldn't be taken at face value. This is far from replacing doctors in anything.

Gatsky 7y ago
Those criticisms aside, if this system went up against the current status quo in a prospective study, there is a reasonable chance it would be on par at least with humans. Whether that makes it a worthwhile endeavour comes down to questions of cost, technical complexity and health outcomes. This last part is actually a significant barrier to 'AI' in healthcare. For that reason, I suspect most companies will prefer to sell their products integrated into assistant style software, where the value proposition is tied to reimbursement eg reporting more scans. The sensitivity is also still not as high as you would like ideally... this is a limitation of mammography.
1e-9 7y ago
1) I see no credible criticism on reddit. 2) I see nothing in the Luke Oakden-Rayner blog that calls this study into question. This study actually avoids the pitfalls that he mentions. 3) This paper said nothing about replacing doctors.