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001472159 019__ $$a1391434292$$a1394923485
001472159 020__ $$a9783031286315
001472159 020__ $$a3031286316
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001472159 020__ $$z9783031286308
001472159 0247_ $$a10.1007/978-3-031-28631-5$$2doi
001472159 035__ $$aSP(OCoLC)1391441631
001472159 040__ $$aEBLCP$$beng$$cEBLCP$$dYDX$$dGW5XE$$dEBLCP$$dOCLCQ$$dSFB
001472159 049__ $$aISEA
001472159 050_4 $$aR858
001472159 08204 $$a610.285$$223/eng/20230801
001472159 24500 $$aAdvanced AI and Internet of Health Things for Combating Pandemics /$$cMohamed Lahby, Virginia Pilloni, Jyoti Sekhar Banerjee, Mufti Mahmud, editors.
001472159 260__ $$aCham :$$bSpringer International Publishing AG,$$c2023.
001472159 300__ $$a1 online resource (xiv, 397 pages) :$$billustrations (chiefly color).
001472159 336__ $$atext$$btxt$$2rdacontent
001472159 337__ $$acomputer$$bc$$2rdamedia
001472159 338__ $$aonline resource$$bcr$$2rdacarrier
001472159 4901_ $$aInternet of Things
001472159 5050_ $$aIntro -- Preface -- Contents -- About the Editors -- Part I State-of-the-Art -- Knowledge Graphs for COVID-19: A Survey -- 1 Introduction -- 2 Background -- 2.1 Knowledge Graph -- 2.2 Transformer -- 2.2.1 Bidirectional Encoder Representations from Transformers (BERT) -- 3 Knowledge Graph Construction -- 3.1 Entity Extraction -- 3.2 Relation Extraction -- 3.3 Knowledge Fusion/Coreference Resolution -- 3.4 Knowledge Graph Storage -- 3.5 Knowledge Graph Visualization -- 4 Application of Knowledge Graphs in Covid-19 -- 5 Challenges in Knowledge Graph Construction
001472159 5058_ $$a5.1 Quality of Knowledge Graph Construction -- 5.2 Visualizing a Knowledge Graph -- 6 Conclusion -- References -- Mapping Effective Practices and Frameworks During the AEC Industry's Combat with COVID-19: Scientometric Analysis -- 1 Introduction -- 1.1 Research Gap and Objective -- 2 Research Method -- 2.1 Phase One: Searching Publications -- 2.2 Screening -- 2.3 Data Analysis -- 2.4 Scientometric Analysis -- 2.5 Thematic Analysis -- 3 Results of Scientometric Analysis -- 3.1 Number of Publications and Citations -- 3.2 Publication Source -- 3.3 Origin of Publications -- 3.4 Keywords Analysis
001472159 5058_ $$a3.5 Co-occurrence of Keywords Analysis -- 3.6 Author Co-citation Network -- 3.7 Active Countries -- 3.8 Most-Cited Publications -- 4 Results of Thematic Analysis -- 4.1 Technology Solutions for COVID-19 -- 4.2 Management Frameworks for Health Technology -- 4.3 Educational Technology -- 5 Discussion -- 6 Conclusion -- References -- Deep Learning for Combating COVID-19 Pandemic in Internet of Medical Things (IoMT) Networks: A Comprehensive Review -- 1 Introduction -- 2 Wireless Body Sensor Networks -- 3 The WBSN Architecture -- 4 WBSN Applications -- 4.1 Telemedicine and Remote Patient Monitoring
001472159 5058_ $$a4.2 Rehabilitation and Therapy -- 4.3 Biofeedback -- 4.4 Assisted Living Technologies -- 5 Main Challenges of WBSNs -- 6 Health Surveillance System -- 6.1 Biosensor Devices -- 6.2 Gateway Device -- 6.3 Back-End Component -- 7 Data Gathering and Fusion -- 8 The Covid-19 Pandemic -- 9 Telemedicine, Remote Patient Monitoring, and Decision Making -- 10 Covid-19 Pandemic Combating: Deep Learning Approaches -- 10.1 Convolutional Neural Network (CNN) -- 10.2 Recurrent Neural Network (RNN)) -- 10.3 LSTM (Long Short-Term Memory) -- 10.4 GAN -- 10.5 Auto-Encoder-Decoder -- 11 Discussions
001472159 5058_ $$a12 Conclusions -- References -- Part II Machine Learning and COVID-19 Pandemic -- Machine Learning Algorithms for Classification of COVID-19 Using Chest X-Ray Images -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Pre-processing -- 3.2 Feature Extraction -- 3.3 Classification Techniques -- 3.3.1 Naïve Baye Classifier -- 3.3.2 Decision Tree Classifier -- 3.3.3 KNN Classifier -- 3.3.4 Logistic Regression -- 3.3.5 ANN Classifier -- 4 Result and Discussion -- 4.1 Dataset Description -- 4.2 Performance Matrix -- 5 Overall Performance Accuracy -- 6 Conclusions -- References
001472159 506__ $$aAccess limited to authorized users.
001472159 520__ $$aThis book presents the latest research, theoretical methods, and novel applications in the field of Health 5.0. The authors focus on combating COVID-19 or other pandemics through facilitating various technological services. The authors discuss new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 or other pandemic based on machine intelligence models and communication technologies. The aim of the coverage is to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence and Internet of Medical Things (IoMT). This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics. Present discoveries in artificial intelligence techniques and machine learning and deep learning models for combating COVID-19; Provides an overview of practical and simulation concepts of Internet of Medical Things (IoMT) technologies; Proposes frameworks related to the detection and analysis of COVID-19 based on AI and IoMT; .
001472159 588__ $$aDescription based upon print version of record.
001472159 650_0 $$aMedical informatics.
001472159 650_0 $$aPandemics$$xData processing.
001472159 650_0 $$aArtificial intelligence$$xMedical applications.
001472159 650_0 $$aInternet of things.
001472159 655_0 $$aElectronic books.
001472159 7001_ $$aLahby, Mohamed.
001472159 7001_ $$aPilloni, Virginia.
001472159 7001_ $$aBanerjee, Jyoti Sekhar.
001472159 7001_ $$aMahmud, Mufti.
001472159 77608 $$iPrint version:$$aLahby, Mohamed$$tAdvanced AI and Internet of Health Things for Combating Pandemics$$dCham : Springer International Publishing AG,c2023$$z9783031286308
001472159 830_0 $$aInternet of things.
001472159 852__ $$bebk
001472159 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-28631-5$$zOnline Access$$91397441.1
001472159 909CO $$ooai:library.usi.edu:1472159$$pGLOBAL_SET
001472159 980__ $$aBIB
001472159 980__ $$aEBOOK
001472159 982__ $$aEbook
001472159 983__ $$aOnline
001472159 994__ $$a92$$bISE