AI-assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities: Third EAI International Conference, AISCOVID-19 2022, Braga, Portugal, ... and Telecommunications Engineering, 485)
معرفی کتاب «AI-assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities: Third EAI International Conference, AISCOVID-19 2022, Braga, Portugal, ... and Telecommunications Engineering, 485)» نوشتهٔ José Manuel Machado (editor), Hugo Peixoto (editor)، منتشرشده توسط نشر Springer Nature Switzerland AG در سال 2023. این کتاب در فرمت pdf، زبان انگلیسی ارائه شده است.
This 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. Preface Organization Contents COVID-19 Global Impact Not Necessarily Relaxed: How Work Interruptions Affect Users' Perception of Stress in Remote Work Situations 1 Introduction 1.1 Current Situation 1.2 Related Work 1.3 Research Objective 2 Methodology 2.1 Laboratory Experiment and Eye-Tracking 2.2 Qualitative Interviews 2.3 Evaluation of Data 3 Results and Discussion 3.1 Hypothesis and Justifications 3.2 Further Findings, Coping Strategies and Recommendations 4 Limitations 4.1 Limitations of the Work Situation 4.2 Limitations Regarding the Experiment 4.3 Limitations Regarding Comparability with the TSST 5 Conclusion References COVID-19 Cases and Their Impact on Global Air Traffic 1 Introduction and Motivation 2 Related Work 2.1 Impact of Coronavirus (COVID-19) Pandemic on Air Transport Mobility, Energy, and Environment: A Case Study ch21 2.2 Estimating and Projecting Air Passenger Traffic During the COVID-19 Coronavirus Outbreak and Its Socio-Economic Impact ch22 2.3 Global Impact of COVID-19 Pandemic on Road Traffic Collisions ch23 3 Materials and Methods 3.1 Data Sources 3.2 Data Transformation Layer 3.3 Data Visualization Layer 4 Results 5 Conclusions and Future Work References The Impact of Contingency Measures on the COVID-19 Reproduction Rate 1 Introduction 2 Background 3 Materials and Methods 3.1 Big Data Architecture 4 Results 5 Conclusions and Future Work References AI Applied to COVID-19 Business Intelligence Platform for COVID-19 Monitoring: A Case Study 1 Introduction 2 Background 3 Methodology 4 Business Analytics Platform 4.1 Project Planning 4.2 Business Requirements 4.3 Technological Architecture 4.4 Dimensional Modelling 4.5 Data ETL Design 4.6 Analytical Application Development 4.7 Implementation and Growth 5 Conclusion and Future Work References First Clustering Analysis of COVID in Portugal 1 Introduction 2 Background 2.1 COVID-19 2.2 Portuguese Reality of COVID-19 2.3 Project ioCOVID19 2.4 Data Mining 2.5 Clustering 2.6 Similar Works 3 Materials and Methods 3.1 Design Science Research 3.2 CRISP-DM 3.3 DSR and CRISP-DM 3.4 Tools 4 Case Study 4.1 Business Understanding 4.2 Data Understanding 4.3 Data Preparation 5 Modeling 6 Results 7 Discussion 8 Conclusion References Multichannel Services for Patient Home-Based Care During COVID-19 1 Introduction 2 Background 2.1 Agency for Integration, Diffusion and Archive of Medical Information (AIDA) 3 Materials 4 Multichannel Services Implemented During COVID-19 4.1 COVID-19 Workflow 4.2 Multichannel Model Implemented 4.3 CHUP Monit 4.4 Telephone Contact 4.5 Aida Contingency 5 Results 6 Discussion 7 Conclusions References Machine Learning In Healthcare Steps Towards Intelligent Diabetic Foot Ulcer Follow-Up Based on Deep Learning 1 Introduction and Contextualization 2 Background 2.1 Diabetes and Wound Classification 2.2 Clinical Decision Support Systems 2.3 Deep Learning 2.4 Convolutional Neural Networks 3 State of the Art 4 Results 4.1 Proposed Architecture 5 Discussion 6 Conclusions References Recommendation of Medical Exams to Support Clinical Diagnosis Based on Patient's Symptoms 1 Introduction 2 Related Work 3 Methodology 3.1 Business Understanding 3.2 Data Understanding 3.3 Data Preparation 3.4 Modeling 3.5 Evaluation 4 Results and Discussion 5 Conclusion References Author Index
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