This is horrendously incorrect. Surgical masks do not filter aerosolized particles at the same effiency as an N95. For an airborn virus, that's a pretty big deal, especially for HCP who are constantly exposed to high viral loads.
When worn normally, or when well sealed? Are there tests of this? If they are both melt blown fabric then it seems at least plausible that this thing could work. It should be tested of course, but it seems like they are in the process of doing that.
Thanks. For those not following the link, this study shows that NaCl aerosols penetrate measured surgical masks at a much higher rate than n95 masks, even after creating a firm seal.
It is hard to tell what exactly was tested in this study. It mentions the standards which the tested respirators met but there is no mention of any standards regarding the tested surgical masks. Were they surgical masks that met the ASTM standards for surgical masks? If so the level 1, 2 or 3 standards?
The solution Save The Face Mask proposes is designed to work with surgical masks which meet ASTM standards. Given the lack of information regarding the masks tested the quoted study is fairly useless in evaluating the proposed solution.
> Discussion: Neither surgical nor cotton masks effectively filtered SARS–CoV-2 during coughs by infected patients. Prior evidence that surgical masks effectively filtered influenza virus (1) informed recommendations that patients with confirmed or suspected COVID-19 should wear face masks to prevent transmission (2). However, the size and concentrations of SARS–CoV-2 in aerosols generated during coughing are unknown. Oberg and Brousseau (3) demonstrated that surgical masks did not exhibit adequate filter performance against aerosols measuring 0.9, 2.0, and 3.1 μm in diameter. Lee and colleagues (4) showed that particles 0.04 to 0.2 μm can penetrate surgical masks. The size of the SARS–CoV particle from the 2002–2004 outbreak was estimated as 0.08 to 0.14 μm (5); assuming that SARS-CoV-2 has a similar size, surgical masks are unlikely to effectively filter this virus.
> Of note, we found greater contamination on the outer than the inner mask surfaces.
Isn't the whole point of the apparatus we are discussing to create a better seal with a surgical mask? The study another person linked to here hot-glued the masks being tested to their testing appliance, which does seem to create a seal.
Tbh I don't know anything about it. Their blog post seems technical and well-thought out. They aren't offering these things for sale at $50 a pop, so they're not trying to gouge the public. They are going through the necessary testing. It doesn't seem like an effort that can be slapped down with internet comment outrage.
> Surgical masks do not filter aerosolized particles at the same effiency as an N95. For an airborn virus, that's a pretty big deal,
Last I heard, COVID-19 transmission by aerosols vs. droplets was controversial, and only droplet rather than airborne precautions are generally seen as necessary for it.
Also, a big reason (but, yes, not the only one) that surgical masks are less effective against aerosols is that they don't tightly seal, so the most effective part is routinely bypassed by aerosols.
That's what we thought a month or so ago. The science with SARS-CoV-2 is developing, and currently we think people need to be careful with large and small droplets. Large droplets fall out of the air quickly; small droplets can be blown further.
The infectious dose for covid-19 is very small, so getting hit by a few large droplets or more small droplets is about the same.
There's no real standard definition for "aerosol" which makes these conversations trickier.
Sure, one is certified by a professional body (NIOSH etc) and the other is not. Since it's not, the burden of proof in this case is one sided.
For example:
"Surgical N95 respirators are approved by NIOSH as to their respiratory protection efficiency and resistance and other NIOSH requirements. They are also separately cleared by FDA as medical devices. FDA clears surgical masks for sale in the United States but does not test and certify the respirator."
The EULA is attached up the drivers. Newer versions of CUDA often require newer drivers, so you bump into the issue regardless of when you buy the GPU.
"Required" fields that are no longer required, and "optional" fields that are no longer optional are basically 6 of one and half a dozen of another.
I'm personally strongly in the "required" camp because at least the interface makes an attempt at giving clues to a user as to what fields are important. If everything is optional, there's no information being passed as to what is important anymore.
This is a good comment, but I think it's worth emphasizing that this is the difference between "7 orders of magnitude" and "6 orders of magnitude". It doesn't in any way invalidate the point in the comment it is replying to.
MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io
At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.
We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.
If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.
MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io
At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.
We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.
If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.
MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA
At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the HW, translational expertise, and financial support to execute on our mission.
We're hiring for multiple roles on our ML, SW, Product, Data Eng, and Infrastructure teams. If interested, feel free to reach out (contact info in profile).
I sent you an email two months ago, and asked about a follow up last month (after which I sent an email). So here's another follow up (with which I'll also send another email) in the hopes that you see it. Would love to talk to you about the kind of work you do, specifically with ML and how you use actual clinical data
MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io
At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.
We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.
If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.
Hey,
I emailed you around this time last month when you posted the ad in the November Who's Hiring, but haven't heard anything back. Also sent a follow up email a few weeks ago. Would you like me to resend my email?
MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io
At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.
We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.
If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.
