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AI-assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities: Third EAI International Conference, AISCOVID-19 2022, Braga, Portugal, November 16-18, 2022, Proceedings: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, cartea 485

Editat de José Manuel Machado, Hugo Peixoto
en Limba Engleză Paperback – 30 iul 2023
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.
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Specificații

ISBN-13: 9783031382031
ISBN-10: 303138203X
Ilustrații: IX, 101 p. 38 illus., 33 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.17 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Locul publicării:Cham, Switzerland

Cuprins

COVID-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.