Abstract Machine learning (ML) has proven to be a useful technology for data analysis and
modeling in a wide variety of domains, including food science and engineering. The use of …

Big data analysis has found applications in many industries due to its ability to turn huge
amounts of data into insights for informed business and operational decisions. Advanced …

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 …

With advances in artificial intelligence (AI) technologies, the development and
implementation of digital food systems are becoming increasingly possible. There is …

Food-borne diseases have a high worldwide occurrence, substantially impacting public
health and the social economy. Most food-borne diseases are contagious or poisonous and …

Food safety plays an essential role in our daily lives, and it becomes serious with the
development of worldwide trade. To tackle the food safety issues, many advanced …

The big data revolution presents an exciting frontier to expand public health research,
broadening the scope of research and increasing the precision of answers. Despite these …

In various application domains/sectors, data collected from the respective industries are
complemented with open data providing added value to the overall analysis and decision …

Foodborne outbreaks are a serious but preventable threat to public health that often lead to
illness, loss of life, significant economic loss, and the erosion of consumer confidence …

Precision public health has been defined as using multi‐level and relatively novel data types
(such as patient‐provided digital data from internet applications and digital medical records) …