"AI, 코로나 무증상자 기침 소리로 가려낸다" MIT VIDEO: AI can detect COVID-19 from the sound of your cough

AI can detect COVID-19 from the sound of your cough

By Yasemin Saplakoglu - Staff Writer 6 hours ago

The algorithm listens to subtle differences in coughs between healthy people and infected people.

People with COVID-19 who are asymptomatic can spread the disease without any outward signs that they're sick. But a newly developed AI, with a keen algorithmic ear, might be able to detect asymptomatic cases from the sounds of people's coughs, according to a new study.

"AI, 코로나 무증상자 기침 소리로 가려낸다"  MIT   COVID-19를 앓고 있는 사람들은 그들이 아프다는 어떤 외적인 징후도 없이 병을 퍼뜨릴 수 있다. 그러나 새로운 연구에 따르면 알고리즘적인 귀가 예민한 새로 개발된 AI는 사람들의 기침 소리로부터 무증상 감염자를 감지할 수 있을 것이라고 한다. MIT의 한 연구팀은 최근 건강한 사람과 감염된 사람 사이의 기침의 미묘한 차이를 들어줌으로써 증상이 없는 COVID-19 사례를 감지할 수 있는 인공지능 모델을 개발했다. 연구진은 현재 임상시험에서 AI를 테스트하고 있으며 이미 식약청의 검진 도구로 사용할 수 있도록 승인을 구하는 절차에 착수했다. 이 알고리즘은 팀이 폐렴, 천식, 심지어 기억 상실 상태인 알츠하이머병과 같은 질병을 감지하기 위해 개발한 이전 모델을 기반으로 하고 있는데, 이것은 성대 약화와 호흡기 성능 저하와 같은 신체 내 다른 기능 저하를 일으킬 수도 있다. 실제로 연구원들이 COVID-19를 검출하기 위해 적응한 것은 알츠하이머 모델이다. "말하는 소리와 기침 소리는 성대와 주변 장기의 영향을 받는다."고 MIT 오토ID 연구소의 공동저자인 브라이언 수비라나가 발표문에서 말했다.  "우리가 유창한 말솜씨에서 쉽게 얻을 수 있는 것들은, AI는 단순히 기침, 즉 그 사람의 성별, 모국어, 심지어 감정 상태 같은 것들로 부터 얻을 수 있다. 기침을 하는 방법에는 사실 감정이 내재되어 있다." 황기철 콘페이퍼 에디터 Ki Chul Hwang Conpaper editor curator

edited by kcontents

A group of researchers at MIT recently developed an artificial intelligence model that can detect asymptomatic COVID-19 cases by listening to subtle differences in coughs between healthy people and infected people. The researchers are now testing their AI in clinical trials and have already started the process of seeking approval from the Food and Drug Administration (FDA) for it to be used as a screening tool.

The algorithm is based on previous models the team developed to detect conditions such as pneumonia, asthma and even Alzheimer's disease, a memory-loss condition that can also cause other degradation in the body such as weakened vocal cords and respiratory performance. 

Indeed, it is the Alzheimer's model that the researchers adapted in an effort to detect COVID-19. "The sounds of talking and coughing are both influenced by the vocal cords and surrounding organs," co-author Brian Subirana, a research scientist in MIT's Auto-ID Laboratory said in a statement. "Things we easily derive from fluent speech, AI can pick up simply from coughs, including things like the person's gender, mother tongue or even emotional state. There's in fact sentiment embedded in how you cough." 

The Conversation

edited by kcontents

First, they created a website where volunteers — both healthy and those with COVID-19 — could record coughs using their cellphones or computers; they also filled out a survey with questions about their diagnosis and any symptoms they were experiencing. People were asked to record "forced coughs," such as the cough you let out when your doctor tells you to cough while listening to your chest with a stethoscope.

Through this website, the researchers gathered more than 70,000 individual recordings of forced-cough samples, according to the statement. Of those, 2,660 were from patients who had COVID-19, with or without symptoms. They then used 4,256 of the samples to train their AI model and 1,064 of the samples to test their model to see whether or not it could detect the difference in coughs between COVID-19 patients and healthy people. 

They found that their AI was able to pick up differences in the coughs related to four features specific to COVID-19 (which were also used in their Alzheimer's algorithm) — muscular degradation, vocal cord strength, sentiment such as doubt and frustration and respiratory and lung performance. 

The sound of a cough

The AI model correctly identified 98.5% of people with COVID-19, and correctly ruled out COVID-19 in 94.2% of people without the disease. For asymptomatic people, the model correctly identifed 100% of people with COVID-19, and correctly ruled out COVID-19 in 83.2% of people without the disease.

These are "a pretty encouraging set of numbers," and the results are "very interesting," said Dr. Anthony Lubinsky, the medical director of respiratory care at NYU Langone Tisch Hospital who was not a part of the study. 

Pharmaphorum

edited by kcontents

But "whether or not this performs well enough in a real-world setting to recommend its use as a screening tool would need further study," Lubinsky told Live Science. What's more, further research is needed to ensure the AI would accurately evaluate coughs from people of all ages and ethnicities, he said (The authors also mention this limitation in their paper). 

If a doctor were to listen to the forced cough of a person with asymptomatic COVID-19, they likely wouldn't be able to hear anything out of the ordinary. It's "not a thing that a human ear would be easily able to do," Lubinsky said. Though follow-up studies are definitely needed, if the software proves effective, this AI — which will have a linked app if approved — could be "very useful" for finding asymptomatic cases of COVID-19, especially if the tool is cheap and easy to use, he added.

The AI can "absolutely" help curb the spread of the pandemic by helping to detect people with asymptomatic disease, Subirana told Live Science in an email. The AI can also detect the difference between people who have other illnesses such as the flu and those who have COVID-19, but it's much better at distinguishing COVID-19 cases from healthy cases, he said.

The team is now seeking regulatory approval for the app that incorporates the AI model, which may come within the next month, he said. They are also testing their AI in clinical trials in a number of hospitals around the world, according to the paper.

View full text

https://www.livescience.com/asymptomatic-coronavirus-detection-ai.html

Detecting COVID-19 Through Cough Sounds - Ingenious Talks

 kcontents