Foodborne Disease Risk Prediction Using Multigraph Structural Long Short-term Memory Networks: Algorithm Design and Validation Study.

Yi Du Hanxue Wang Wenjuan Cui Hengshu Zhu Yunchang Guo Fayaz Ali Dharejo Yuanchun Zhou

Published in: JMIR medical informatics (2021)

The spatial-temporal risk prediction model can take into account the spatial-temporal characteristics of foodborne disease data and accurately determine future disease spatial-temporal risks, thereby providing support for the prevention and risk assessment of foodborne disease.

Keyphrases

risk assessment
machine learning
working memory
heavy metals
big data
climate change