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D&D Coronavirus thread

Discussion in 'BBS Hangout: Debate & Discussion' started by NewRoxFan, Feb 23, 2020.

  1. rocketsjudoka

    rocketsjudoka Contributing Member
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    Again if it was about something that’s been around for a long time with few side effects we would’ve seen universal acceptance of masking.
     
  2. Amiga

    Amiga I get vaunted sacred revelations from social media
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    Vaccination and treatment of disease aren't exclusive. They both are of value, and having excellent vaccines does not stop treatments. We see that with probably every known disease in the world that has good to excellent vaccines.

    I no longer follow covid19 treatment closely, but I believe one of the promising treatments was monoclonal antibody - last I remember, it went from an infusion process to a pill (so much easier to administer). If I remember, that's Regenero imdevimab and casirivimab injection drugs. However, the drawback of that treatment is studies show that it's not very effective against new variants (not surprising since the manufactured antibodies take time to make, and by the time it's available, it can quickly be "outdated"). It's also *new* but not *new* - so the same arguments can be made (long term side effects? - not likely but not 100% for sure either; short term side effects -- relatively higher risk given not many people have gone through this treatments). It also must be administered before serious complication (hospitalization). Other than that, I don't recall there was any good treatment options for covid.

    ps. I have a relative that went through monoclonal antibody treatment (infusion) in Feb. He caught covid about 10 days after his first Pfizer-BioNTech vaccine. Because of his age, dr recommended the treatment. Only had minor covid symptoms. Not sure if it's the treatment or the vaccine or both... but of course, at the time, the manufactured antibodies match the prevalent strain.
     
  3. Two Sandwiches

    Two Sandwiches Contributing Member

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    Fair point. As I said, some people are just morons. Lol
     
  4. London'sBurning

    London'sBurning Contributing Member

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    As durvasa has pointed out already, the healthcare industry has explored it. Thus your anecdotes you're sharing as affirmation to it's effectiveness. I will always be for more options that helps ensure the health and safety of more of my neighbors. That said, I don't necessarily have the same confidence you do that Ivermectin is a viable alternative solution over vaccination and likely annual booster shots.

    As a person who likes to be lazy with my own health, I'm not personally a fan of ingesting more medication than I absolutely have to unless I absolutely have to. I hope to keep that trend for as long as I possibly can until my health defaults me no other choice. If someone offers me a shot I can take once a year over periodically taking an oral medication, I know which I will choose every single time.
     
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  5. durvasa

    durvasa Contributing Member

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    Perhaps I should read up more on it. What I’ve read/heard from others is that the evidence that it is effective is pretty thin at this point.
     
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  6. Two Sandwiches

    Two Sandwiches Contributing Member

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    Once again, a very small study that I wish could be reproduced on a much wider scale, but there are multiple of these.

    https://www.medrxiv.org/content/10.1101/2021.03.26.21254398v1
     
  7. pahiyas

    pahiyas Member

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    In general:
    If you are sick, where do you go to to get better? MEDICAL SCIENCE.
    What does the MAJORITY of Medical Science advise with regards to vaccines? EXACTLY.

    I don't get the vaccine hesitancy of some educated people unless they think they knew better about medical science.
     
    Andre0087 and FranchiseBlade like this.
  8. Invisible Fan

    Invisible Fan Contributing Member

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    Kind of a weird title/article when machine learning shouldn't be considered AI but that distinction is never made clear between the editors nor the researchers using the tool. Real AI wouldn't need to be spoonfed quality data for a virus people haven't encountered before.

    https://www.technologyreview.com/20...-ai-failed-covid-hospital-diagnosis-pandemic/
    Hundreds of AI tools have been built to catch covid. None of them helped.

     
  9. Invisible Fan

    Invisible Fan Contributing Member

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    Waiting a year is actually prudent for a new and unapproved vaccine. Problem is we all saw light at the end of the tunnel and ran for it. I didn't mind being waitlisted because at least I had 3 months to see if anything showed up like Astrazeneca's adverse side effects.

    The issue is that people want to go out, then think their risk profile is the same as last year if they mask up but don't vax up.

    There were helluva lot less people during quarantine when masking was the only game in town. But hey, some beach towns were a-ok last year and that didn't stop them from throwing up their middle fingers...

    Anyways, I hope the cruelty and bitterness shown in the last part of the article mellows out as more people are affected. People are wound up by what they read to the point where they ignore people they see around them. The dignity we afford upon others ultimately returns back when we or the people we know make our own mistakes.
     
  10. vlaurelio

    vlaurelio Contributing Member

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    “Artificial intelligence is essentially a system that seems smart. That’s not a very good definition, though, because it’s like saying that something is ‘healthy’. What exactly does that mean?” she says. “On a basic level, artificial intelligence is where a machine seems human-like and can imitate human behavior.”

    These behaviors include problem-solving, learning, and planning, for example, which are achieved through analyzing data and identifying patterns within it in order to replicate those behaviors.

    Machine learning, on the other hand, is a type of artificial intelligence, Edmunds says. “Where artificial intelligence is the overall appearance of being smart, machine learning is where machines are taking in data and learning things about the world that would be difficult for humans to do,” she says. “ML can go beyond human intelligence.”

    https://www.northeastern.edu/gradua...nce-vs-machine-learning-whats-the-difference/
     
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  11. Invisible Fan

    Invisible Fan Contributing Member

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    Fair enough. I just think Machine Learning can overrate people's idea of what AI can do. Hand feeding quality data until it brings out some desired outcome plus the amount of care and resources needed to make it work is still a bit like a dude operating inside the Mechanical Turk. In today's context it'd be replacing thousands of people, but not necessarily.

    Reality sometimes does not match investor hype.
     
  12. vlaurelio

    vlaurelio Contributing Member

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    its not really handfeeding.. its just massive amounts of data are analyzed

    there cannot be AI without data

    the smartest person knows the most information
     
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  13. Invisible Fan

    Invisible Fan Contributing Member

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    What went wrong
    Many of the problems that were uncovered are linked to the poor quality of the data that researchers used to develop their tools. Information about covid patients, including medical scans, was collected and shared in the middle of a global pandemic, often by the doctors struggling to treat those patients. Researchers wanted to help quickly, and these were the only public data sets available. But this meant that many tools were built using mislabeled data or data from unknown sources.

    Driggs highlights the problem of what he calls Frankenstein data sets, which are spliced together from multiple sources and can contain duplicates. This means that some tools end up being tested on the same data they were trained on, making them appear more accurate than they are.

    It also muddies the origin of certain data sets. This can mean that researchers miss important features that skew the training of their models. Many unwittingly used a data set that contained chest scans of children who did not have covid as their examples of what non-covid cases looked like. But as a result, the AIs learned to identify kids, not covid.

    Driggs’s group trained its own model using a data set that contained a mix of scans taken when patients were lying down and standing up. Because patients scanned while lying down were more likely to be seriously ill, the AI learned wrongly to predict serious covid risk from a person’s position.

    In yet other cases, some AIs were found to be picking up on the text font that certain hospitals used to label the scans. As a result, fonts from hospitals with more serious caseloads became predictors of covid risk.

    Errors like these seem obvious in hindsight. They can also be fixed by adjusting the models, if researchers are aware of them. It is possible to acknowledge the shortcomings and release a less accurate, but less misleading model. But many tools were developed either by AI researchers who lacked the medical expertise to spot flaws in the data or by medical researchers who lacked the mathematical skills to compensate for those flaws.

    A more subtle problem Driggs highlights is incorporation bias, or bias introduced at the point a data set is labeled. For example, many medical scans were labeled according to whether the radiologists who created them said they showed covid. But that embeds, or incorporates, any biases of that particular doctor into the ground truth of a data set. It would be much better to label a medical scan with the result of a PCR test rather than one doctor’s opinion, says Driggs. But there isn’t always time for statistical niceties in busy hospitals.

    That hasn’t stopped some of these tools from being rushed into clinical practice. Wynants says it isn’t clear which ones are being used or how. Hospitals will sometimes say that they are using a tool only for research purposes, which makes it hard to assess how much doctors are relying on them. “There’s a lot of secrecy,” she says.

    Wynants asked one company that was marketing deep-learning algorithms to share information about its approach but did not hear back. She later found several published models from researchers tied to this company, all of them with a high risk of bias. “We don’t actually know what the company implemented,” she says.

    According to Wynants, some hospitals are even signing nondisclosure agreements with medical AI vendors. When she asked doctors what algorithms or software they were using, they sometimes told her they weren’t allowed to say.
     
  14. vlaurelio

    vlaurelio Contributing Member

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    yeah AI is just as good as the data it uses

    no data no AI

    bad data bad AI
     
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  15. No Worries

    No Worries Contributing Member

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  16. No Worries

    No Worries Contributing Member

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  17. MojoMan

    MojoMan Member

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  18. tinman

    tinman Contributing Member
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    We should have chip implants in people in the future to have real time monitoring
     
  19. NewRoxFan

    NewRoxFan Contributing Member

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  20. Commodore

    Commodore Contributing Member

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