LEADER 04242nam 22007455 450 001 9910736021103321 005 20251113191546.0 010 $a9783031382048 010 $a3031382048 024 7 $a10.1007/978-3-031-38204-8 035 $a(MiAaPQ)EBC30668852 035 $a(Au-PeEL)EBL30668852 035 $a(DE-He213)978-3-031-38204-8 035 $a(PPN)272251747 035 $a(CKB)27878696000041 035 $a(OCoLC)1391989914 035 $a(EXLCZ)9927878696000041 100 $a20230729d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAI-assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities $eThird EAI International Conference, AISCOVID-19 2022, Braga, Portugal, November 16-18, 2022, Proceedings /$fedited by José Manuel Machado, Hugo Peixoto 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (106 pages) 225 1 $aLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering,$x1867-822X ;$v485 311 08$aPrint version: Machado, José Manuel AI-Assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities Cham : Springer,c2023 9783031382031 327 $aCOVID-19 Global Impact -- Not Necessarily Relaxed: How Work Interruptions affect Users? Perception of Stress in Remote Work Situations -- COVID-19 cases and their impact on global air traffic -- The Impact of contingency measures on the COVID-19 reproduction rate -- AI applied to COVID-19 -- Business Intelligence Platform for COVID-19 Monitoring: A Case Study -- First Clustering Analysis of COVID in Portugal -- Multichannel services for patient home-based care during COVID-19 -- Machine Learning In Healthcare -- Steps Towards Intelligent Diabetic Foot Ulcer Follow-up based on Deep Learning -- Recommendation of Medical Exams to Support Clinical Diagnosis based on Patient?s Symptoms. 330 $aThis book constitutes the refereed post-conference proceedings of the Third International Conference on AI-assisted Solutions for COVID-19 and Biometrical Applications in Smart Cities, AISCOVID-19 2022, held in November 2022 in Braga, Portugal. The 8 full papers of AISCOVID-19 2022 were carefully selected from 21 submissions and present a comprehensive and up-to-date look at the intersection of COVID-19, big data, machine learning, deep learning, and healthcare. The theme of AISCOVID-19 2022 was Healthcare effective and efficient Solutions for COVID-19 that can be achieved using Artificial Intelligence and Computer-Assisted paradigms. 410 0$aLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering,$x1867-822X ;$v485 606 $aMedical informatics 606 $aData structures (Computer science) 606 $aInformation theory 606 $aCoding theory 606 $aApplication software 606 $aInformation storage and retrieval systems 606 $aHealth Informatics 606 $aData Structures and Information Theory 606 $aCoding and Information Theory 606 $aComputer and Information Systems Applications 606 $aInformation Storage and Retrieval 615 0$aMedical informatics. 615 0$aData structures (Computer science) 615 0$aInformation theory. 615 0$aCoding theory. 615 0$aApplication software. 615 0$aInformation storage and retrieval systems. 615 14$aHealth Informatics. 615 24$aData Structures and Information Theory. 615 24$aCoding and Information Theory. 615 24$aComputer and Information Systems Applications. 615 24$aInformation Storage and Retrieval. 676 $a610.285 676 $a610.285 700 $aMachado$b Jose? Manuel$00 701 $aPeixoto$b Hugo$01380271 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910736021103321 996 $aAI-Assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities$93421554 997 $aUNINA