Data Science for COVID-19 (inbunden)
Format
Häftad (Paperback / softback)
Språk
Engelska
Utgivningsdatum
2021-10-25
Förlag
Elsevier Science & Technology
Medarbetare
Gupta, Deepak (Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, India) (red.) / de Albuquerque, Victor Hugo Costa, MSc, PhD (Professor and Senior Researcher, Federal University of Ceara, Fortaleza, Graduate Program on Teleinformati
Dimensioner
235 x 190 x 41 mm
Vikt
1371 g
ISBN
9780323907699

Data Science for COVID-19

Volume 2: Societal and Medical Perspectives

Häftad,  Engelska, 2021-10-25
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Finns även som
Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques, including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes is now possible.

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Övrig information

Dr. Utku Kose is an Associate Professor at Süleyman Demirel University, Turkey. He received his PhD from Selcuk University, Turkey, in the field of computer engineering. He has more than 100 publications to his credit, including Deep Learning for Medical Decision Support Systems, Springer; Artificial Intelligence Applications in Distance Education, IGI Global; Smart Applications with Advanced Machine Learning and Human-Centered Problem Design, Springer; Artificial Intelligence for Data-Driven Medical Diagnosis, DeGruyter; Computational Intelligence in Software Modeling, DeGruyter; Data Science for Covid-19, Volumes 1 and 2, Elsevier/Academic Press; and Deep Learning for Medical Applications with Unique Data, Elsevier/Academic Press, among others. Dr. Kose is a Series Editor of the Biomedical and Robotics Healthcare series from Taylor & Francis/CRC Press. His research interests include artificial intelligence, machine ethics, artificial intelligence safety, optimization, chaos theory, distance education, e-learning, computer education, and computer science. Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 11 years. He is presently working as Assistant Professor in Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab, India in May 2018. He has completed his M. Tech. from VIT University, Vellore, Tamil Nadu, India and B. Tech. from RGPV, Bhopal, Madhya Pradesh, India. He has completed his PDF from UNIFOR, Brazil. He has published around 105 research papers along with book chapters including more than 25 papers in SCI indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited eleven books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/Guest Editor and many more positions in various conferences and journals. His research interest include machine learning, deep learning for biomedical health informatics, educational technologies, and computer vision. Victor Hugo C. de Albuquerque [M'17, SM'19] is a collaborator Professor and senior researcher at the Graduate Program on Teleinformatics Engineering at the Federal University of Ceará, Brazil, and at the Graduate Program on Telecommunication Engineering, Federal Institute of Education, Science and Technology of Ceará, Fortaleza/CE, Brazil. He has a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is a specialist, mainly, in Image Data Science, IoT, Machine/Deep Learning, Pattern Recognition, Robotic. Dr. Ashish Khanna has 16 years of expertise in teaching, entrepreneurship, and research and development. He received his PhD from the National Institute of Technology, Kurukshetra, India, and completed a post-doc degree at the National Institute of Telecommunications (Inatel), Brazil. He has published around 40 SCI-indexed papers in 'IEEE Transactions', and in other reputed journals by Springer, Elsevier, and Wiley, with a cumulative impact factor of above 100. He has published around 90 research articles in top SCI/Scopus journals, conferences, and book chapters. He is co-author or editor of numerous books, including 'Advanced Computational Techniques for Virtual Reality in Healthcare' (Springer), 'Intelligent Data Analysis: From Data Gathering to Data Comprehension' (Wiley), and 'Hybrid Computational Intelligence: Challenges and Applications' (Elsevier). His research interests include distributed systems, MANET, FANET, VANET, Internet of Things, and machine learning. He is one of the founders of Bhavya Publications and the Universal Innovator Lab, which is actively involved in research, in...