Искусственный интеллект
Oct. 30th, 2020 09:46 pm![[personal profile]](https://www.dreamwidth.org/img/silk/identity/user.png){kind=small}
chuka_lisОказывается, может определить "асимптоматичный ковид". Без теста на коронавирус.
Как?
А просто. Смартофон отслеживает кашель владельца. И по типу кашля и его частоте делает "вывод" (основываясь на данных по тем, у кого есть и тест, и симптомы).
И угадывает с точностью 98.5%!
Такой вот асимптоматичный ковид, кашель ведь не является симптомом ковида, ну или респираторного заболевания, а те кто кашляют- якобы, выходит, асимптоматичные и здоровые.
The team used the 2,500 Covid-associated recordings, along with 2,500 more recordings that they randomly selected from the collection to balance the dataset. They used 4,000 of these samples to train the AI model. The remaining 1,000 recordings were then fed into the model to see if it could accurately discern coughs from Covid patients versus healthy individuals.
The model identified 98.5 percent of coughs from people confirmed with Covid-19, and of those, it accurately detected all of the asymptomatic coughs.
The team is working on incorporating the model into a user-friendly app, which if FDA-approved and adopted on a large scale could potentially be a free, convenient, noninvasive prescreening tool to identify people who are likely to be asymptomatic for Covid-19. A user could log in daily, cough into their phone, and instantly get information on whether they might be infected and therefore should confirm with a formal test.
Как?
А просто. Смартофон отслеживает кашель владельца. И по типу кашля и его частоте делает "вывод" (основываясь на данных по тем, у кого есть и тест, и симптомы).
И угадывает с точностью 98.5%!
Такой вот асимптоматичный ковид, кашель ведь не является симптомом ковида, ну или респираторного заболевания, а те кто кашляют- якобы, выходит, асимптоматичные и здоровые.
The team used the 2,500 Covid-associated recordings, along with 2,500 more recordings that they randomly selected from the collection to balance the dataset. They used 4,000 of these samples to train the AI model. The remaining 1,000 recordings were then fed into the model to see if it could accurately discern coughs from Covid patients versus healthy individuals.
The model identified 98.5 percent of coughs from people confirmed with Covid-19, and of those, it accurately detected all of the asymptomatic coughs.
The team is working on incorporating the model into a user-friendly app, which if FDA-approved and adopted on a large scale could potentially be a free, convenient, noninvasive prescreening tool to identify people who are likely to be asymptomatic for Covid-19. A user could log in daily, cough into their phone, and instantly get information on whether they might be infected and therefore should confirm with a formal test.
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