Precision Medicine implies a deep understanding of inter-individual differences in health
and disease that are due to genetic and environmental factors. To acquire such …

Food safety continues to threaten public health. Machine learning holds potential in
leveraging large, emerging data sets to improve the safety of the food supply and mitigate …

Background 'Big data'has great potential to help address the global health challenge of
obesity. However, lack of clarity with regard to the definition of big data and frameworks for …

Interest in conceptualizing, measuring, and applying social network analysis (SNA) in public
health has grown tremendously in recent years. While these studies have broadened our …

Background Obesity is a leading cause of preventable death worldwide. Artificial
intelligence (AI), characterized by machine learning (ML) and deep learning (DL), has …

Background Eating disorders affect an increasing number of people. Social networks
provide information that can help. Objective We aimed to find machine learning models …

This paper develops the notion of “open data product”. We define an open data product as
the open result of the processes through which a variety of data (open and not) are turned …

Context Most dietary assessment methods are limited by self-report biases, how long they
take for participants to complete, and cost of time for dietitians to extract content …

Background The ownership of patient information in the context of big data is a relatively
new problem, which is not yet fully recognized by the medical academic community. The …

Background Academic interest in the use of social media data is rapidly increasing. The
application of social media analysis in various domains is an emerging trend due to a …