
Recent Trends in Healthcare Innovation
Description
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Drawing on research contributions from experts in academia, industry, and healthcare institutions worldwide, this volume highlights technological breakthroughs in medicine, their implications for patient care, and their potential to reshape the future of global healthcare. It explores collaborative frameworks between technology providers and healthcare practitioners to address pressing healthcare challenges and improve overall public health outcomes. The peer-reviewed papers contained in this book address critical themes in healthcare innovation, with a focus on:
integration of artificial intelligence and machine learning in medical diagnostics
advancements in telemedicine and wearable technologies
innovations in public health and epidemiology
sustainable healthcare practices
This is a valuable resource for healthcare professionals, researchers, academics, and students specializing in healthcare innovation, biomedical engineering, and public health. It is also ideal for policymakers, technologists, and industry leaders interested in leveraging emerging technologies for enhanced healthcare delivery.
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Persons
Francesco Flammini received his masters (2003) and doctoral (2006) degrees in Computer Engineering from the University of Naples Federico II, Italy. He is currently a Professor of Computer Science with a focus on Cyber-Physical Systems at Maelardalen University (Sweden). He has been a Senior Lecturer and the chair of the Cyber-Physical Systems group at Linnaeus University (Sweden). He has worked for almost 15 years in private and public companies, including Ansaldo STS (now Hitachi Rail) and IPZS (Italian State Mint and Polygraphic Institute), on large international projects addressing intelligent transportation systems, critical infrastructure protection and cybersecurity, as a technical leader and unit head. He is an IEEE Senior Member and the Chair of the IEEE SMC Technical Committee on Homeland Security. He is also a member of the ERCIM Working Group on Formal Methods for Industrial Critical Systems (FMICS), He has (co)authored 100+ scientific publications and he has served as a chair, invited speaker, steering/program committee member, and editor for several international conferences and journals.
Ravi Kumar V, Professor and Head, Department of Information Science and Engineering has about 24 years of teaching experience. Professor obtained his B.E in Electrical and Electronics Engineering from Kuvempu University, M. Tech in Computer Science & Engineering, and PhD from VTU. He has 27 publications to his credit in reputed publications and has served as an editor for the titles "Intelligent Systems in Healthcare and Disease Identification using Data Science" and "The Convergence of IoT with Blockchain Technology". He has received "Best Teacher" for the academic year 2021-22 by VVCE. He was a Program Chair of Annual International Conference on Machine Learning, Data Science and Blockchain technology (AICDMB) 2020 & 2021. He has also received Rs. 1.6 Lakhs fund from AICTE, Govt. of India to organize International Conference. He is an Editorial Board Member of Inderscience International Journal of Blockchain and Cryptocurrencies and reviewer for different international conferences and reputed Journals. His research interests include Artificial Intelligence, NLP, Blockchain Technology, Cloud Computing, Big Data, Data Mining, and Internet of Things.
Prema N S, working as Associate Professor, Information Science and Engineering, VVCE in Karnataka, India, with a total teaching experience of 19 years. She graduated in Information Science from SJCE, Mysore, and received her M.Tech. degree in Software Engineering from SJCE. She went on to receive her Ph.D at VTU, India. Her research interests include medical datamining, datamining, knowledge engineering, natural language processing, and machine learning. She has authored 20+ publications in international journals, conferences, and patents. She has published her work in reputed international journals and served as a reviewer for national and international journals and conferences.
Content
2. AI and ML applications
3. Regression models application
4. Data analysis
5. Reviews
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