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020 _a9783030601881
_9978-3-030-60188-1
024 7 _a10.1007/978-3-030-60188-1
_2doi
050 4 _aTK5101-5105.9
072 7 _aTJK
_2bicssc
072 7 _aTEC041000
_2bisacsh
072 7 _aTJK
_2thema
082 0 4 _a621.382
_223
245 1 0 _aArtificial Intelligence and Machine Learning for COVID-19
_h[electronic resource] /
_cedited by Fadi Al-Turjman.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aX, 266 p. 105 illus., 91 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v924
505 0 _aSmart Technologies for COVID-19: The Strategic Approaches in Combating the Virus -- A Review on COVID-19 -- Artificial Intelligence in the Face of the Corona Virus Pandemic -- Digital Transformation and Emerging Technologies for COVID-19 Pandemic: Social, Global and Industry Perspectives -- A Deep Analysis and Prediction of COVID-19 in India: Using Ensemble Regression Approach -- Image Enhancement in Healthcare Applications: A Review -- DEEP LEARNING APPROACH USING 3D-ImpCNN CLASSIFICATION FOR CORONAVIRUS DISEASE -- Drone-based Social Distancing, Sanitisation, Inspection, Monitoring and Control Room for COVID-19 -- Application of AI Techniques for COVID-19 in IoT and Big-Data Era: A Survey -- APPLICATION OF IoT, AI and 5G IN the FIGHT AGAINST the COVID-19 PENDAMIC -- AI techniques for Resource Management during Covid-19.
520 _aThis book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies. Includes advances related to COVID-19 diagnosis and tracking through artificial intelligence and machine learning; Enriches the fields of AI and ML with new and innovative operational ideas aimed at aiding in efforts to combat and track COVID-19; Pertains to researchers, scientists, engineers, and practitioners in the field of computing and smart cities technologies.
650 0 _aTelecommunication.
650 0 _aMedical informatics.
650 0 _aArtificial intelligence.
650 0 _aMedicine, Preventive.
650 0 _aHealth promotion.
650 1 4 _aCommunications Engineering, Networks.
650 2 4 _aHealth Informatics.
650 2 4 _aArtificial Intelligence.
650 2 4 _aHealth Promotion and Disease Prevention.
700 1 _aAl-Turjman, Fadi.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030601874
776 0 8 _iPrinted edition:
_z9783030601898
776 0 8 _iPrinted edition:
_z9783030601904
830 0 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v924
856 4 0 _uhttps://doi.org/10.1007/978-3-030-60188-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c177990
_d177990