{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T15:37:55Z","timestamp":1772725075732,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684048","type":"print"},{"value":"9781643684055","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,6,22]],"date-time":"2023-06-22T00:00:00Z","timestamp":1687392000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,22]]},"abstract":"<jats:p>Coronavirus can lead to respiratory illnesses ranging from mild to severe, and even death, which makes early detection critical. However, current COVID-19 (Coronavirus Disease 2019) detection methods are not only expensive but also time-consuming. This poses a challenge, especially with an increasing number of patients and demand for testing kits. Waiting for test results for a few days is not ideal, as the outbreak can spread quickly in the meantime. To address this issue, we propose a COVID-19 prediction infrastructure using deep learning. This innovative android-based application uses a Convolutional Neural Network model, trained on a custom dataset with an accuracy of 97 percent, to predict whether COVID-19 is present or not. With this fast and low-cost approach, users can quickly detect COVID-19 and take appropriate actions to reduce the risk of transmission.<\/jats:p>","DOI":"10.3233\/aise230020","type":"book-chapter","created":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T11:04:56Z","timestamp":1687518296000},"source":"Crossref","is-referenced-by-count":2,"title":["COVID-19 Prediction Infrastructure Using Deep Learning"],"prefix":"10.3233","author":[{"given":"Zahra","family":"Abbas","sequence":"first","affiliation":[{"name":"Institute of Information Technology, Quaid-i-Azam University, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mario","family":"Fiorino","sequence":"additional","affiliation":[{"name":"ICAR-CNR, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Syed Muhammad","family":"Naqi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Quaid-i-Azam University, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Musarat","family":"Abbas","sequence":"additional","affiliation":[{"name":"Department of Electronics, Quaid-i-Azam University, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Ambient Intelligence and Smart Environments","Workshop Proceedings of the 19th International Conference on Intelligent Environments (IE2023)"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/AISE230020","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T23:34:46Z","timestamp":1687563286000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/AISE230020"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,22]]},"ISBN":["9781643684048","9781643684055"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/aise230020","relation":{},"ISSN":["1875-4163","1875-4171"],"issn-type":[{"value":"1875-4163","type":"print"},{"value":"1875-4171","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,22]]}}}