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dc.contributor.authorStergiou, Konstantinos D.-
dc.contributor.authorMinopoulos, Georgios-
dc.contributor.authorMemos, Vasileios A.-
dc.contributor.authorStergiou, Christos-
dc.contributor.authorKoidou, Maria P.-
dc.contributor.authorPsannis, Kostas E.-
dc.date.accessioned2022-10-27T06:47:42Z-
dc.date.available2022-10-27T06:47:42Z-
dc.date.issued2022-
dc.identifier10.3390/app122110766en_US
dc.identifier.issn2076-3417en_US
dc.identifier.urihttps://doi.org/10.3390/app122110766en_US
dc.identifier.urihttps://ruomo.lib.uom.gr/handle/7000/1529-
dc.description.abstractToday, healthcare system models should have high accuracy and sensitivity so that patients do not have a misdiagnosis. For this reason, sufficient knowledge of the area is required, with the medical staff being able to validate the correctness of their decisions. Therefore, artificial intelligence (AI) in combination with other emerging technologies could provide many benefits in the medical sector. In this paper, we demonstrate the combination of Internet of Things (IoT) and cloud computing (CC) with AI-related techniques such as artificial intelligence (AI), machine learning (ML), deep learning (DL), and neural networks (NN) in order to provide a useful approach for scientists and doctors. Our proposed model makes use of these immersive technologies so as to provide epidemic forecasting and help accelerate drug and antibiotic discovery.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceApplied Sciencesen_US
dc.subjectFRASCATI::Engineering and technologyen_US
dc.subject.otherartificial intelligenceen_US
dc.subject.otherdeep learningen_US
dc.subject.otherdrug discoveryen_US
dc.subject.otherepidemic diseasesen_US
dc.subject.otherforecastingen_US
dc.subject.othermachine learningen_US
dc.subject.otherneural networksen_US
dc.titleA Machine Learning-Based Model for Epidemic Forecasting and Faster Drug Discoveryen_US
dc.typeArticleen_US
dc.contributor.departmentΤμήμα Εφαρμοσμένης Πληροφορικήςen_US
local.identifier.volume12en_US
local.identifier.issue21en_US
local.identifier.firstpage10766en_US
local.identifier.volumetitleApplication of Data Analytics in Smart Healthcareen_US
Εμφανίζεται στις Συλλογές: Τμήμα Εφαρμοσμένης Πληροφορικής

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