About 40% of individuals who tested positive for the novel coronavirus infection never, ever feel sick, the Centers for Disease Control and Prevention (CDC) estimates in its updated guidelines. It remains a puzzle as to why presymptomatic transmitters and asymptomatic cases appear so frequently. While other viruses that cause flu and common cold also spread silently, SARS-CoV-2's extreme evasiveness makes it harder to control. First off, there is a possibility that there are fewer true asymptomatic cases than we think. Studies do not follow COVID-19 patients for a significant period post-testing to find out if they might have developed symptoms later on.
Researchers at MIT say they've developed an algorithm that can diagnose COVID-19 by the sound of someone's cough, even if that person is asymptomatic. In a paper published in the IEEE Journal of Engineering in Medicine and Biology, the team reports that their approach distinguishes between infected and healthy individuals through "forced-cough" recordings contributed via smartphones, laptops, and other mobile devices. Applying AI to discern the cause of a cough isn't a new idea. Last year, a group of Australian researchers developed a smartphone app that could ostensibly identify respiratory disorders like pneumonia and bronchitis by "listening" to a person's exhalations. The potential for bias exists in these systems -- algorithms trained on imbalanced or unrepresentative datasets can lead to worse health outcomes for certain user groups -- but studies suggest they could be a useful tool on the front lines of the coronavirus pandemic.
The aim of the AI algorithm is to separate healthy patients from ill but asymptomatic ones based on coughing tone, feeling, and other biomarkers. In a continuation of the involvement of artificial intelligence (AI) in healthcare, a new app may help diagnose asymptomatic COVID-19 carriers through a simple listening test -- a cough from someone infected versus a regular cough. It may seem straight from science fiction, but a research team at MIT believes that asymptomatic carriers may be showing subtle signs through the sound of their cough. They've built an app, programming it with thousands of data points from healthy and sick volunteers. AI was able to identify coughs coming from those infected with the virus with a 98.5% accuracy rate.
The National Institute of Infectious Diseases has said in a study that the coronavirus may have continued to spread unnoticed through carriers with mild or no symptoms after the outbreak from March to April receded once. The recently released study suggested that such a phenomenon may have led to the resurgence of COVID-19 infections in and after June, when Japan began resuming economic activities. In the study, which ran through July 16, the institute collected coronavirus samples from some 3,700 patients and analyzed the genome sequence. Because a virus undergoes mutations during the course of infection, the institute deduced how COVID-19 spread by looking at how the virus changed. The genome analysis found that the so-called European type of the virus spread widely in Japan in and after March but waned in late May thanks to preventive measures.
A CT scan of the chest of a 66-year-old male reveals patchy rounded hazy spots throughout the lungs. He had tested positive for the coronavirus and experienced shortness of breath. A CT scan of the chest of a 66-year-old male reveals patchy rounded hazy spots throughout the lungs. He had tested positive for the coronavirus and experienced shortness of breath. Even if someone is infected by the novel coronavirus and remains asymptomatic -- free of coughing, fever, fatigue and other common signs of infection, that doesn't mean the coronavirus isn't taking a toll.