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A global race is underway to discover a vaccine, drug, or combination of treatments that can disrupt the SARS-CoV-2 virus. The problem is, there are more than a billion such molecules. A researcher would conceivably want to test each one against the two dozen or so proteins in SARS-CoV-2 to see their effects. Such a project could use every wet lab in the ...


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I will interpret the questions as being about triage. This is particularly important in crisis situations, where a lot of such life-or-death decisions have to be taken. In the START system there are four different categories: the deceased, who are beyond help the injured who could be helped by immediate transportation the injured with less severe injuries ...


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At face value, this sound monstrous--a measure to offload responsibility to a non-conscious mechanism that cannot be meaningfully punished for mistakes. However, I will argue: There is humane benefit in taking this decision out of the hands of doctors re: the psychological toll Specifically, doctors are not the reason for resource scarcity, yet they're ...


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Oliver's answer is interesting and it provides valuable information (such as a brief description of the triage process, which I was not aware of), but I disagree with his conclusion or, at least, I think it can be misleading because he is implying it's "more ethical" because the AI will behave in "more principled way". It depends on your ...


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I disagree with the idea that a trained Machine Learning model would be impartial. Models are trained on data sets that contain features. Humans prepare those data sets and decide what features are included in the data set. The model only knows what it is trained on. Human bias is still there just less blatantly obvious. To address your question directly, ...


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According to the Baidu Research's blog post How Baidu is harnessing the power of AI in the battle against coronavirus (12-03-2020), there are already some artificial intelligence tools or algorithms being used to fight the coronavirus. Given that I cannot confirm that these AI tools and algorithms I will mention are really being used in practice, I will only ...


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There are already a couple of papers in the literature that attempt to provide a taxonomy and survey of adversarial attacks. I will just list the two that I think are reliable enough that you can probably use as a reference. A taxonomy and survey of attacks against machine learning (2019) by Nikolaos Pitropakis et al., published in Computer Science Review ...


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I'm not sure if it is being used directly in the industry, but here is an interesting article on research being done by 3 UK universities using AI.


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There's a strong sentiment towards the idea that medical diagnosis is largely Abductive Reasoning. See this presentation for additional details. One approach to automated abductive reasoning is parsimonious covering theory. If you want a relatively in-depth look at all of this, check out the book Abductive Inference Models for Diagnostic Problem-Solving . ...


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I wouldn't focus only on "deep learning" unless you have some specific reason for doing so. There may be other techniques which could be as effective, or more effective. One approach I've seen used for something similar was Inductive Logic Programming. For one example of using ILP to reason about elements of biochemistry, see this paper That's not ...


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Not really something that slows it down but currently Mauricio Santillana at Harvard is working on modeling the pandemic and has shared some of his approaches. He explained that they have used google search trends to try to predict the number of actual cases (there is a delay between people being sick and getting tested). Looking for search terms like, "how ...


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It's already being done, and apparently with very good results. See: Predicting Risk of Suicide Attempts Over Time Through Machine Learning, Walsh, Ribiero, Franklin Here is the abstract from the paper: Traditional approaches to the prediction of suicide attempts have limited the accuracy and scale of risk detection for these dangerous behaviors. We ...


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