ResearchArticle Virtual Healthcare Center for COVID-19 Patient Detection Based on Artificial Intelligence Approaches Seifeddine Messaoud , 1 Soulef Bouaafia , 1 Amna Maraoui , 1 Lazhar Khriji , 2 Ahmed Chiheb Ammari , 2 and Mohsen Machhout 1 1 Laboratory of Electronics and Microelectronics, Faculty of Sciences, University of Monastir, Monastir, Tunisia 2 Department of Electrical and Computer Engineering, College of Engineering, Sultan Qaboos University, Muscat, Oman CorrespondenceshouldbeaddressedtoSeifeddineMessaoud;seifeddine.messaoud@fsm.rnu.tn Received 19 May 2021; Accepted 22 December 2021; Published 11 January 2022 AcademicEditor:MariamArabi Copyright©2022SeifeddineMessaoudetal.isisanopenaccessarticledistributedundertheCreativeCommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Attheendof2019,theinfectiouscoronavirusdisease(COVID-19)wasreportedforthefirsttimeinWuhan,and,sincethen,ithas become a public health issue in China and even worldwide. is pandemic has devastating effects on societies and economies aroundtheworld,andpoorcountriesandcontinentsarelikelytofaceparticularlyseriousandlong-lastingdamage,whichcould leadtolargeepidemicoutbreaksbecauseofthelackoffinancialandhealthresources.eincreasingnumberofCOVID-19tests givesmoreinformationabouttheepidemicspread,andthiscanhelpcontainthespreadtoavoidmoreinfection.AsCOVID-19 keeps spreading, medical products, especially those needed to perform blood tests, will become scarce as a result of the high demandandinsufficientsupplyandlogisticalmeans.However,technologicaltestsbasedondeeplearningtechniquesandmedical imagescouldbeusefulinfightingthispandemic.Inthisperspective,weproposeaCOVID-19diseasediagnosis(CDD)toolthat implements a deep learning technique to provide automatic symptoms checking and COVID-19 detection. Our CDD scheme implementstwomainsteps.First,thepatient’ssymptomsarechecked,andtheinfectionprobabilityispredicted.en,basedon the infection probability, the patient’s lungs will be diagnosed by an automatic analysis of X-ray or computerized tomography (CT)images,andthepresenceoftheinfectionwillbeaccordinglyconfirmedornot.enumericalresultsprovetheefficiencyof the proposed scheme by achieving an accuracy value over 90% compared with the other schemes. 1. Introduction e new coronavirus disease (COVID-19) appeared at the end of December 2019 in Wuhan city of China and has affectedmostofcountriesaroundtheworld[1,2].COVID- 19iscausedbythenovelsevereacuterespiratorysyndrome coronavirus 2 (SARS-CoV-2) and represents the causative agentofapotentiallyfataldisease,makingitaglobalpublic health concern. In this context, person-to-person COVID- 19infectiontransmissionhasledtotheisolationofpatients who are subsequently administered a variety of treatments. In general, COVID-19 is an acutely resolved disease, but it can also be fatal, with a high fatality rate. AsofAugust25,2020,nearly815,113COVID-19victims have died, while the total number of infected subjects was approximately 23,652,302 cases. is is caused by SARS- COV-2,currentlyspreadallovertheworld[3].eoutbreak began in Mainland China, with a geographic concentration inWuhanCity,Hubei.However,onFebruary26,2020,the rate of increase in cases became higher in the rest of the world compared to that in China. Large outbreaks are oc- curring on a daily basis in Italy (69,176 cases), the United States (51,914 cases), and Iran (24,811 cases), and the geo- graphic spread of the epidemic continues. e respiratory transmission of the disease from one person to another has caused the epidemic to spread rapidly, where the most common infection signs include respiratory issues, fever, cough, symptoms, and dyspnea. Giventhehighnumberofinfectionsandblockagesatthe hospitallevel,thisdiseasecanbemortalasaresultofdelayed Hindawi Canadian Journal of Infectious Diseases and Medical Microbiology Volume 2022, Article ID 6786203, 15 pages https://doi.org/10.1155/2022/6786203