Could we use ML to detect Covid-19 infection?
One of machine learning's best tricks is in classification. We use it for everything from image search to automated driving. This makes it a classic fit for infection detection as there's only 2 options: infected or not. What I'm thinking is that we could train a model against the hundreds of thousands of testing kits now in circulation with known results, wire that model into a web API, and then patch a device like this one: https://ift.tt/2lCwPqc into said API. You send a breath/spit sample to the server, and the server would respond with a yes/no based on the model. We could use this to test more people, more often, effectively for $0 24h/day. Doctors can be tested throughout their shifts, attendees for events could be tested before allowing entry, people could be easily vetted for exiting quarantine too. I'm a web developer, and am confident that the web API part would be easy and anonymous, and from what I know about ML, training a model like this probably isn't difficult... if you have the data. What I don't know much about is how easy it is to convert biology to data: getting testing kit information into a model, and converting breath/spit into data. I don't know how easy this is, but if it's doable, we may have something seriously helpful. Can someone with domain knowledge in this area chime in with their point of view? 1 comments on Hacker News.
One of machine learning's best tricks is in classification. We use it for everything from image search to automated driving. This makes it a classic fit for infection detection as there's only 2 options: infected or not. What I'm thinking is that we could train a model against the hundreds of thousands of testing kits now in circulation with known results, wire that model into a web API, and then patch a device like this one: https://ift.tt/2lCwPqc into said API. You send a breath/spit sample to the server, and the server would respond with a yes/no based on the model. We could use this to test more people, more often, effectively for $0 24h/day. Doctors can be tested throughout their shifts, attendees for events could be tested before allowing entry, people could be easily vetted for exiting quarantine too. I'm a web developer, and am confident that the web API part would be easy and anonymous, and from what I know about ML, training a model like this probably isn't difficult... if you have the data. What I don't know much about is how easy it is to convert biology to data: getting testing kit information into a model, and converting breath/spit into data. I don't know how easy this is, but if it's doable, we may have something seriously helpful. Can someone with domain knowledge in this area chime in with their point of view?
One of machine learning's best tricks is in classification. We use it for everything from image search to automated driving. This makes it a classic fit for infection detection as there's only 2 options: infected or not. What I'm thinking is that we could train a model against the hundreds of thousands of testing kits now in circulation with known results, wire that model into a web API, and then patch a device like this one: https://ift.tt/2lCwPqc into said API. You send a breath/spit sample to the server, and the server would respond with a yes/no based on the model. We could use this to test more people, more often, effectively for $0 24h/day. Doctors can be tested throughout their shifts, attendees for events could be tested before allowing entry, people could be easily vetted for exiting quarantine too. I'm a web developer, and am confident that the web API part would be easy and anonymous, and from what I know about ML, training a model like this probably isn't difficult... if you have the data. What I don't know much about is how easy it is to convert biology to data: getting testing kit information into a model, and converting breath/spit into data. I don't know how easy this is, but if it's doable, we may have something seriously helpful. Can someone with domain knowledge in this area chime in with their point of view? 1 comments on Hacker News.
One of machine learning's best tricks is in classification. We use it for everything from image search to automated driving. This makes it a classic fit for infection detection as there's only 2 options: infected or not. What I'm thinking is that we could train a model against the hundreds of thousands of testing kits now in circulation with known results, wire that model into a web API, and then patch a device like this one: https://ift.tt/2lCwPqc into said API. You send a breath/spit sample to the server, and the server would respond with a yes/no based on the model. We could use this to test more people, more often, effectively for $0 24h/day. Doctors can be tested throughout their shifts, attendees for events could be tested before allowing entry, people could be easily vetted for exiting quarantine too. I'm a web developer, and am confident that the web API part would be easy and anonymous, and from what I know about ML, training a model like this probably isn't difficult... if you have the data. What I don't know much about is how easy it is to convert biology to data: getting testing kit information into a model, and converting breath/spit into data. I don't know how easy this is, but if it's doable, we may have something seriously helpful. Can someone with domain knowledge in this area chime in with their point of view?
Hacker News story: Could we use ML to detect Covid-19 infection?
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March 18, 2020
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