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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/2431| AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App | |
| Ali Imran. Iryna Posokhova. Haneya N. Qureshi. Usama Masood. Sajid Riaz. Kamran Ali. Charles N. John. Muhammad Nabeel. | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| https://arxiv.org/pdf/2004.01275v4.pdf | |
| 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. | |
| arxiv.org | |
| 2020 | |
| Artículo | |
| https://arxiv.org/pdf/2004.01275v4.pdf | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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