Healthcare and Knowledge Management for Society 5.0 (eBook, PDF)
Trends, Issues, and Innovations
Redaktion: Kansal, Vineet; Wickramasinghe, Nilmini; Tiwari, Rajdev; Sinha, Sapna; Ranjan, Raju
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Healthcare and Knowledge Management for Society 5.0 (eBook, PDF)
Trends, Issues, and Innovations
Redaktion: Kansal, Vineet; Wickramasinghe, Nilmini; Tiwari, Rajdev; Sinha, Sapna; Ranjan, Raju
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Healthcare and knowledge management is the need of the era; this book investigates various challenges faced by practitioners in this area. It also covers the work to be done in the healthcare sector and the use of different computing techniques for better insight and decision-making.
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Healthcare and knowledge management is the need of the era; this book investigates various challenges faced by practitioners in this area. It also covers the work to be done in the healthcare sector and the use of different computing techniques for better insight and decision-making.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 311
- Erscheinungstermin: 27. Dezember 2021
- Englisch
- ISBN-13: 9781000529661
- Artikelnr.: 63068937
- Verlag: Taylor & Francis
- Seitenzahl: 311
- Erscheinungstermin: 27. Dezember 2021
- Englisch
- ISBN-13: 9781000529661
- Artikelnr.: 63068937
Vineet Kansal is a professor at Institute of Engineering Technology, a constituent college of Dr APJ Abdul Kalam Technical University, Lucknow, India. He has done B.Tech. (Computer Science & Engineering) from G B Pant University Agriculture & Technology, Pantnagar, and, M.Tech. and Ph.D. from Indian Institute of Technology (IIT) Delhi. Currently, he is Pro Vice Chancellor of Dr. A. P. J. Abdul Kalam Technical University. Dr Kansal has been in academics for more than 28 years. He has taught different computer science courses to B.Tech., MCA and M.Tech. students. Dr Kansal has supervised Masters and Doctoral students' research work. He has published several research papers in reputed journals, conferences, book chapters apart from being Book editor. His area of research interest includes Data Analytics, Machine Learning, Artificial Intelligence, Networking, Cloud Computing, Big Data Analytics and Optimization. Raju Ranjan, PhD is currently the Professor in School of Computing Science & Engineering at Galgotias University, India. He received his Ph.D. in the area of Data Mining from Uttarakhand Technical University, India. He also earned his M. Tech. in Computer Science from JRN University, India. He also holds Master of Physics from Magadh University, India. Professor Ranjan has over twenty years of experience as an academician. Earlier he was associated with Department of Computer Science & Engineering at Greater Noida Institute of Technology, Greater Noida, India. He also served Ideal Institute of Technology, Ghaziabad as HOD of Computer Science & Engineering department. He also worked in Graphic Era Institute of Technology (Now Graphic Era University, Dehradun), and Priyadarshini College of Computer Sciences. His research interests include Data Mining, IoT and Cyber Security. He holds an Australian patent for secure communication among IoT devices and an Indian patent for automatic prevention of fluid clogging. He has published over 25 research papers in international journals & conferences and some book chapters. He has delivered keynote speeches at various conferences. He also reviewed several articles for prominent international journals. He has guided several under-graduate and post-graduate students in various research projects of Databases, Computer Graphics, Networking and Cyber Security. He is also guiding PhD students from Galgotias University Sapna Sinha is an Associate Professor in Amity Institute of Information Technology, Amity University Uttar Pradesh, Noida. She has 20+ years of teaching experience in teaching UG and PG computer science courses. She is Ph.D. in Computer Science and Engineering from Amity University. She has authored several book chapters and research papers in journal of repute. Machine Learning, Big Data Analytics, Artificial Intelligence, Networking and Security is her area of Interest. She is D-Link certified Switching and Wireless professional, she is also Microsoft Technology Associate in Database management system, Software Engineering and Networking. She is EMC Academic Associate in Cloud Infrastructure Services. https://orcid.org/0000-0002-2504-8030 Rajdev Tiwari is a committed academician with around 20 years of experience at premier engineering colleges of Uttar Pradesh like KNIT Sultanpur, IPEC Ghaziabad, ABESIT Ghaziabad, NIET Greater Noida etc. Currently he is working with GNIOT Greater Noida as Professor and Head Computer Science and Engineering department. He is basically M.Sc in Electronics, MCA and have done PhD in Computer Science. He has also done PGDASDD from CDAC Noida and qualified UGC NET in year 2012. He has been visiting faculty at AMITY University, Noida and at IETE, New Delhi for PhD and ALCCS programs respectively for past many years. He is actively associated with various professional bodies like IEEE, CSI, ISTE etc. He has published more than 30 research papers in various journal of international repute. He has attended and chaired various international conferences. He has delivered keynote speeches at various TEQIP-III FDPs and judged many project exhibitions as technical judge. He has guided around 10 M.Tech dissertations and one PhD. He is guiding 5 PhD scholars from Dr APJAKTU, at present. He has authored two books; one on soft computing published by Acme Learning, and another on Algorithms published by Pearson. He is on the panel of various International Journals as Editor/Reviewer. He has received various grants for Research Project, Conferences & FDPs from reputed organizations like DrAPJ AKTU, Lucknow & AICTE, New Delhi. Nilmini Wickramasinghe, MBA PhD, is currently the Professor of Digital Health and the Deputy Director of the Iverson Health Innovation Research Institute at Swinburne University of Technology and inaugural Professor - Director Health Informatics Management at Epworth HealthCare. She also holds honorary research professor positions at the Peter MacCallum Cancer Centre and Northern Health. After completing 5 degrees at the University of Melbourne, she was awarded a full scholarship to complete PhD studies at Case Western Reserve University, Cleveland, OH, USA and later she was sponsored to complete executive education at Harvard Business School, Harvard University, Cambridge, MA, USA in Value-based HealthCare. For over 20 years, Professor Wickramasinghe has been actively, researching and teaching within the health informatics/digital health domain in US, Germany and Australia with a particular focus on designing, developing and deploying suitable models, strategies and techniques grounded in various management principles to facilitate the implementation and adoption of technology solutions to effect superior, value-based patient centric care delivery. Professor Wickramasinghe collaborates with leading scholars at various premier healthcare organizations and universities throughout Australasia, US and Europe and is well published with more than 400 referred scholarly articles, more than 15 books, numerous book chapters, an encyclopaedia and a well established funded research track record securing over $25M in funding from grants in US, Australia, Germany and China as a chief investigator. She holds a patent around analytics solution for managing healthcare data and is the editor-in-chief of two scholarly journals published by InderScience: Intl. J. Biomedical engineering and Technology(www.inderscience.com/ijbet) and Intl. J Networking and virtual Organisations(www.inderscience.com/ijnvo) as well as the editor of the Springer book series Healthcare Delivery in the Information Age. She received the prestigious 2020 Alexander von Humboldt award for outstanding contribution to a scientific discipline (Digital Health).
1. Blockchain Technology for Healthcare. 2. Diagnosing Patient Health
Conditions and Improving the Patient Experience: An Application of AI and
ML. 3. Development of Thinking Computer Systems and Machine Learning in
Health Care. 4. Clinical Decision-Making as a Subset of Decision-Making:
Leveraging the Concepts of Decision-Making and Knowledge Management to
Characterize Clinical Decision-Making. 5. Leveraging Artificial
Intelligence in a Human-Centric Society 5.0: A Health Care Perspective. 6.
Blockchain-Based Medical Records for the Health Care Industry. 7.
Blockchain with Corona Virus: Moving Together to Prevent Future Pandemics.
8. Computer Assisted Health Care Framework for Breast Cancer Detection in
Digital Mammograms. 9. Artificial Intelligence and Inpatients' Risk
Vulnerability Assessment - Trends, Challenges, and Applications. 10.
Internet of Gealthcare Things and Block Chain: An Efficient Integration for
Smart Health Care Systems. 11 Comparative Study of Machine Learning
Techniques. 12. Comparative Study of Machine Learning Techniques for Breast
Cancer Diagnisis. 13. Fine-Tuning of Recommender System Using Artificial
Intelligence. 14. Deep Learning in Health Care. 15. Ontology Learning-Based
e-Healthcare System. 16. A New Method for OTP Generation. 17. A Visual
Introduction to Machine Learning, AI Framework, and Architecture. 18.
Evolution of Business Intelligence System: From Ad-Hoc Report to Decision
Support System to Data Lake Based BI 3.0. 19. Novel Deep-Learning
Approaches for Future Computing Applications and Services.
Conditions and Improving the Patient Experience: An Application of AI and
ML. 3. Development of Thinking Computer Systems and Machine Learning in
Health Care. 4. Clinical Decision-Making as a Subset of Decision-Making:
Leveraging the Concepts of Decision-Making and Knowledge Management to
Characterize Clinical Decision-Making. 5. Leveraging Artificial
Intelligence in a Human-Centric Society 5.0: A Health Care Perspective. 6.
Blockchain-Based Medical Records for the Health Care Industry. 7.
Blockchain with Corona Virus: Moving Together to Prevent Future Pandemics.
8. Computer Assisted Health Care Framework for Breast Cancer Detection in
Digital Mammograms. 9. Artificial Intelligence and Inpatients' Risk
Vulnerability Assessment - Trends, Challenges, and Applications. 10.
Internet of Gealthcare Things and Block Chain: An Efficient Integration for
Smart Health Care Systems. 11 Comparative Study of Machine Learning
Techniques. 12. Comparative Study of Machine Learning Techniques for Breast
Cancer Diagnisis. 13. Fine-Tuning of Recommender System Using Artificial
Intelligence. 14. Deep Learning in Health Care. 15. Ontology Learning-Based
e-Healthcare System. 16. A New Method for OTP Generation. 17. A Visual
Introduction to Machine Learning, AI Framework, and Architecture. 18.
Evolution of Business Intelligence System: From Ad-Hoc Report to Decision
Support System to Data Lake Based BI 3.0. 19. Novel Deep-Learning
Approaches for Future Computing Applications and Services.
1. Blockchain Technology for Healthcare. 2. Diagnosing Patient Health
Conditions and Improving the Patient Experience: An Application of AI and
ML. 3. Development of Thinking Computer Systems and Machine Learning in
Health Care. 4. Clinical Decision-Making as a Subset of Decision-Making:
Leveraging the Concepts of Decision-Making and Knowledge Management to
Characterize Clinical Decision-Making. 5. Leveraging Artificial
Intelligence in a Human-Centric Society 5.0: A Health Care Perspective. 6.
Blockchain-Based Medical Records for the Health Care Industry. 7.
Blockchain with Corona Virus: Moving Together to Prevent Future Pandemics.
8. Computer Assisted Health Care Framework for Breast Cancer Detection in
Digital Mammograms. 9. Artificial Intelligence and Inpatients' Risk
Vulnerability Assessment - Trends, Challenges, and Applications. 10.
Internet of Gealthcare Things and Block Chain: An Efficient Integration for
Smart Health Care Systems. 11 Comparative Study of Machine Learning
Techniques. 12. Comparative Study of Machine Learning Techniques for Breast
Cancer Diagnisis. 13. Fine-Tuning of Recommender System Using Artificial
Intelligence. 14. Deep Learning in Health Care. 15. Ontology Learning-Based
e-Healthcare System. 16. A New Method for OTP Generation. 17. A Visual
Introduction to Machine Learning, AI Framework, and Architecture. 18.
Evolution of Business Intelligence System: From Ad-Hoc Report to Decision
Support System to Data Lake Based BI 3.0. 19. Novel Deep-Learning
Approaches for Future Computing Applications and Services.
Conditions and Improving the Patient Experience: An Application of AI and
ML. 3. Development of Thinking Computer Systems and Machine Learning in
Health Care. 4. Clinical Decision-Making as a Subset of Decision-Making:
Leveraging the Concepts of Decision-Making and Knowledge Management to
Characterize Clinical Decision-Making. 5. Leveraging Artificial
Intelligence in a Human-Centric Society 5.0: A Health Care Perspective. 6.
Blockchain-Based Medical Records for the Health Care Industry. 7.
Blockchain with Corona Virus: Moving Together to Prevent Future Pandemics.
8. Computer Assisted Health Care Framework for Breast Cancer Detection in
Digital Mammograms. 9. Artificial Intelligence and Inpatients' Risk
Vulnerability Assessment - Trends, Challenges, and Applications. 10.
Internet of Gealthcare Things and Block Chain: An Efficient Integration for
Smart Health Care Systems. 11 Comparative Study of Machine Learning
Techniques. 12. Comparative Study of Machine Learning Techniques for Breast
Cancer Diagnisis. 13. Fine-Tuning of Recommender System Using Artificial
Intelligence. 14. Deep Learning in Health Care. 15. Ontology Learning-Based
e-Healthcare System. 16. A New Method for OTP Generation. 17. A Visual
Introduction to Machine Learning, AI Framework, and Architecture. 18.
Evolution of Business Intelligence System: From Ad-Hoc Report to Decision
Support System to Data Lake Based BI 3.0. 19. Novel Deep-Learning
Approaches for Future Computing Applications and Services.