Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο:
https://ruomo.lib.uom.gr/handle/7000/1529
Πλήρης εγγραφή μεταδεδομένων
Πεδίο DC | Τιμή | Γλώσσα |
---|---|---|
dc.contributor.author | Stergiou, Konstantinos D. | - |
dc.contributor.author | Minopoulos, Georgios | - |
dc.contributor.author | Memos, Vasileios A. | - |
dc.contributor.author | Stergiou, Christos | - |
dc.contributor.author | Koidou, Maria P. | - |
dc.contributor.author | Psannis, Kostas E. | - |
dc.date.accessioned | 2022-10-27T06:47:42Z | - |
dc.date.available | 2022-10-27T06:47:42Z | - |
dc.date.issued | 2022 | - |
dc.identifier | 10.3390/app122110766 | en_US |
dc.identifier.issn | 2076-3417 | en_US |
dc.identifier.uri | https://doi.org/10.3390/app122110766 | en_US |
dc.identifier.uri | https://ruomo.lib.uom.gr/handle/7000/1529 | - |
dc.description.abstract | Today, 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.iso | en | en_US |
dc.publisher | MDPI | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Applied Sciences | en_US |
dc.subject | FRASCATI::Engineering and technology | en_US |
dc.subject.other | artificial intelligence | en_US |
dc.subject.other | deep learning | en_US |
dc.subject.other | drug discovery | en_US |
dc.subject.other | epidemic diseases | en_US |
dc.subject.other | forecasting | en_US |
dc.subject.other | machine learning | en_US |
dc.subject.other | neural networks | en_US |
dc.title | A Machine Learning-Based Model for Epidemic Forecasting and Faster Drug Discovery | en_US |
dc.type | Article | en_US |
dc.contributor.department | Τμήμα Εφαρμοσμένης Πληροφορικής | en_US |
local.identifier.volume | 12 | en_US |
local.identifier.issue | 21 | en_US |
local.identifier.firstpage | 10766 | en_US |
local.identifier.volumetitle | Application of Data Analytics in Smart Healthcare | en_US |
Εμφανίζεται στις Συλλογές: | Τμήμα Εφαρμοσμένης Πληροφορικής |
Αρχεία σε αυτό το Τεκμήριο:
Αρχείο | Περιγραφή | Μέγεθος | Μορφότυπος | |
---|---|---|---|---|
applsci-12-10766.pdf | 909,3 kB | Adobe PDF | Προβολή/Ανοιγμα |
Αυτό το τεκμήριο προστατεύεται από Αδεια Creative Commons