Regarding the cough identifying AI: Due to the online collection method I suspect that most of the positive samples were already quite advanced in their disease progression. Since Covid-19 deposits in the lungs mainly in the latter part of the disease it is easier to identify them at that point, but also not that useful anymore because most of the transmission happens during the earlier part of the infection (both for symptomatic and asymptomatic people).
These researchers had a much better sample procedure, cough samples were mostly acquired at testing sites, where participants did not know yet whether they have Covid (much less risk of subconscious bias) and were presumably at an earlier stage of their disease. They also had much worse results, which I suspect are more realistic for a real world setting.
What actually needs to be done is to do a longitudinal analysis, i.e. you record your baseline cough when you are healthy. Then if you want to check if you are infected, you cough again and compare that “potentially sick” cough against your baseline “non-covid cough”. The potential of this approach is much higher since baseline characteristics of the cough can be accounted for (smoker, asthmatic, crappy mic in phone).
I have been thinking that it should be possible to gather training data for this quickly by identifying a subset of people that are somewhat likely to get sick in the near future like e.g. people participating in big parties, and acquire coughs from them prior and subsequent to infection. If somebody has ideas how to acquire such data, feel free to share. As an aside, I am somewhat surprised that we as a community interested in AI and out-of-the box thinking have not focused/discussed AI for Covid detection much earlier.
Regarding the cough identifying AI: Due to the online collection method I suspect that most of the positive samples were already quite advanced in their disease progression. Since Covid-19 deposits in the lungs mainly in the latter part of the disease it is easier to identify them at that point, but also not that useful anymore because most of the transmission happens during the earlier part of the infection (both for symptomatic and asymptomatic people).
These researchers had a much better sample procedure, cough samples were mostly acquired at testing sites, where participants did not know yet whether they have Covid (much less risk of subconscious bias) and were presumably at an earlier stage of their disease. They also had much worse results, which I suspect are more realistic for a real world setting.
What actually needs to be done is to do a longitudinal analysis, i.e. you record your baseline cough when you are healthy. Then if you want to check if you are infected, you cough again and compare that “potentially sick” cough against your baseline “non-covid cough”. The potential of this approach is much higher since baseline characteristics of the cough can be accounted for (smoker, asthmatic, crappy mic in phone).
I have been thinking that it should be possible to gather training data for this quickly by identifying a subset of people that are somewhat likely to get sick in the near future like e.g. people participating in big parties, and acquire coughs from them prior and subsequent to infection. If somebody has ideas how to acquire such data, feel free to share. As an aside, I am somewhat surprised that we as a community interested in AI and out-of-the box thinking have not focused/discussed AI for Covid detection much earlier.