Application of Big Data Analysis to Health Risk Assessment
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health Care Sciences".
Deadline for manuscript submissions: 30 December 2025 | Viewed by 1736
Special Issue Editor
Special Issue Information
Dear Colleagues,
Big data analysis is becoming an integral aspect of healthcare advancement. Nowadays, big data are becoming available in large volume. However, the proper use of big data raises a number of unanswered questions and thorny issues.
On the one hand, there are great research opportunities, mostly led by recent technological advancements such as artificial intelligence, data mining and machine learning. On the other hand, the application of big data analysis raises questions about a number of methodological aspects regarding the use of specific algorithms. Another open issue of big data analysis is the proper use of the scientific evidence, in addition to a number of open questions about the ethical use of these data and the protection of the participants’ identity.
Nevertheless, it is important to correctly address the use of big data in health research as the advantages of such a revolution by far outweigh the disadvantages.
The information from large sets of data and the opportunity to merge data from numerous different sources is the way to holistic inference from the population to the individuals. This inference will answer a number of open scientific questions for health prevention and better healthcare.
For this Special Issue of the International Journal of Environmental Research and Public Health, we invite high-quality manuscripts about cutting-edge technologies, methodologies, challenges and scientific evidence about the use of big data for health risk assessment.
Dr. Cristian Ricci
Guest Editor
Manuscript Submission Information
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Keywords
- big data
- risk assessment
- health care
- epidemiology
- public health
- health system
- information technology
- data mining
- machine learning
- AI applications
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