Big Data for eHealth Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: closed (10 May 2022) | Viewed by 61189
Special Issue Editors
Interests: parallel computing; natural language processing; artificial intelligence; deep learning; eHealth; big data analytics; cyber physical systems
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; deep learning; natural language processing; big data analytics; quantum computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the last few years, the rapid growth of the available digitised medical data has opened new challenges for the scientific research community in the healthcare informatic field. In this scenario, the constantly increasing volume of medical data, as well as the complexity and heterogeneity of this kind of data, requires innovative Big Data Analytics methods for extracting valuable insights from them and, at the same time, these new approaches must also guarantee the required levels of privacy and security. These solutions must provide effective and efficient tools to support the daily routine of physicians, medical professionals, and policy makers, improving the quality of the healthcare systems. The recent pandemic emergency has made the need for new Big Data approaches for the processing of such data more urgent.
This Special Issue will be focused on technologies and methodologies in the field of Big Data Analytics for eHealth, also considering their combined use with Internet of Thing (IoT) devices, Artificial Intelligence (AI) methods, and Cyber Security (CS) techniques for the definition of complex systems and architectures for the eHealth domain. A special regard will be paid to papers devoted to the analysis of COVID-19-related Big Data. Contributions can focus on architectures, algorithms, methods; survey papers and reviews are also welcomed.
Dr. Stefano Silvestri
Dr. Francesco Gargiulo
Guest Editors
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Keywords
- eHealth
- Medical Informatics
- Big data Analytics for eHealth
- COVID-19 Big Data Analysis
- Artificial Intelligence in Medicine
- Biomedical Big Data Mining
- Health Information Systems
- Complex Big Data Architectures
- Data-driven Methods
- Security and Privacy of Medical Data
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