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I think in some ways we're thinking of automation in the wrong way. That doesn't have to mean having having an AI doctor, with, you know, a lovely bedside manne
by Brakenshire 13y ago
I think in some ways we're thinking of automation in the wrong way. That doesn't have to mean having having an AI doctor, with, you know, a lovely bedside manner. Reducing the cost of blood tests so that you can do a sweeping diagnosis of 50 problems at once rather than just 10 is a sort of automation - the doctor no longer has to carefully navigate their way through "there's a chance that it is this, but the blood test is expensive, so we'll try something else first". It's automation to analyse blood tests in combination, and look for profiles for diagnosis. It's automation for a patient to have their own smartphone-connected blood pressure monitor, which will alert the surgery if the read-out is dangerous. It's certainly automation to use software image analysis to pick up the presence of cancer cells in tissue biopsies. It's a step-by-step process, it doesn't have to be all at once.
- krakensden 13y agoWant to work on any of the above? Bio-Rad is hiring in the Bay Area.
- Gatsky 13y agoAs other people have commented, augmentation is a very good idea, and automation is part of that. The title of this submission indicates something entirely different to that however. As an aside, the really interesting part of image analysis is not that we can automatically detect tumor cells, but that machine learning can extract features from pathology specimens that a human could never see: http://www.ncbi.nlm.nih.gov/pubmed/23100629 http://www.ncbi.nlm.nih.gov/pubmed/23100629