About: AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App

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About: AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App
Creator	Ali, Kamran Imran, Ali John, Charles Masood, Usama Nabeel, Muhammad »more»
source	ArXiv
abstract	Inability to test at scale has become Achille's heel in humanity's ongoing war against COVID-19 pandemic. An agile, scalable and cost-effective testing, deployable at a global scale, can act as a game changer in this war. To address this challenge, building on the promising results of our prior work on cough-based diagnosis of a motley of respiratory diseases, we develop an Artificial Intelligence (AI)-based test for COVID-19 preliminary diagnosis. The test is deployable at scale through a mobile app named AI4COVID-19. The AI4COVID-19 app requires 2-second cough recordings of the subject. By analyzing the cough samples through an AI engine running in the cloud, the app returns a preliminary diagnosis within a minute. Unfortunately, cough is common symptom of over two dozen non-COVID-19 related medical conditions. This makes the COVID-19 diagnosis from cough alone an extremely challenging problem. We solve this problem by developing a novel multi-pronged mediator centered risk-averse AI architecture that minimizes misdiagnosis. At the time of writing, our AI engine can distinguish between COVID-19 patient coughs and several types of non-COVID-19 coughs with over 90% accuracy. AI4COVID-19's performance is likely to improve as more and better data becomes available. This paper presents a proof of concept to encourage controlled clinical trials and serves as a call for labeled cough data. AI4COVID-19 is not designed to compete with clinical testing. Instead, it offers a complementing tele-testing tool deployable anytime, anywhere, by anyone, so clinical-testing and treatment can be channeled to those who need it the most, thereby saving more lives.
has issue date	2020-04-02(xsd:dateTime)
has license	arxiv
sha1sum (hex)	809572ae170df1c479bf13f406ea8ac7e2045eb4
resource representing a document's title	AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App
resource representing a document's body	covid:809572ae170df1c479bf13f406ea8ac7e2045eb4#body_text
is schema:about of	named entity 'motley' named entity 'humanity' named entity 'minimizes' named entity 'cough' named entity 'extremely' »more»

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