Data Science for Covid-19: Volume 2: Societal and Medical Perspectives
Language: English
Published by Elsevier Science, 2021
- Softcover
- New
Condition: New
£ 235.37
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Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the treatment of the COVID-19 virus Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians.
Seller Inventory # 468112938
- Title
- Data Science for Covid-19: Volume 2: Societal and Medical Perspectives
- Publisher
- Elsevier Science
- Publication year
- 2021
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0323907695
- ISBN 13
- 9780323907699
- Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the treatment of the COVID-19 virus
- Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including the wide variety of impacts the virus is having on societies and medical practice
- Presents insights into innovative, data-oriented modeling and predictive techniques from COVID-19 researchers around the world, including geoprocessing and tracking, lab data analysis, and theoretical views on a variety of technical applications
- Includes real-world feedback and user experiences from physicians and medical staff from around the world for medical treatment perspectives, public safety policies and impacts, sociological and psychological perspectives, the effects of COVID-19 in agriculture, economies, and education, and insights on future pandemics
"Synopsis" may belong to another edition of this title.
About the Author
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.
Ashish Khanna is Professor in Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, India, and is also a Visiting Professor at the University of Valladolid, Spain. His research interests include distributed systems, MANET, FANET, VANET, Internet of Things, and machine learning.
"About the title" may belong to another edition of this title.
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