Big Data, Decision Models, and Public Health

Dear colleagues,

In the digital era, the volume and velocity of environmental, population and public health data from a diverse range of sources are growing rapidly. Big data analytics techniques such as statistical analysis, data mining, machine learning and deep learning can be applied to construct innovative decision models. Decision-making based on concrete evidence is critical and has a substantial impact on public health and program implementation. This fact highlights the important role of decision models under uncertainty, including disease control, health intervention, preventive medicine, health services and systems, health disparities and inequalities, and quality of life, etc. With complex decision making, it can be difficult to comprehend and compare the benefits and risks of all available options to make a decision. This Special Issue focuses on the use of big data analytics and forms of public health decision-making based on the decision model, spanning from theory to practice. While working with people’s health and medical information, we also need to commit to scientific integrity issues including people’s privacy, data sharing, bias and uncertainty, research design and statistical inference. Practical experiences and experiments concerning the above issues in big data analytics are also welcome.

Prof. Dr. Chien-Lung Chan
Prof. Dr. Chi-Chang Chang
Guest Editors

Manuscript Submission Information

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