Resource type:
Blogs/news/opinion
Link:
This review highlights advances in visual analytics applied to food safety risk analysis and prewarning (RAPW). The study categorizes methods across data sources, analysis tasks, and visualization techniques, addressing microbial contamination, fraud detection, and risk prediction. Key insights include integrating machine learning with human-in-the-loop approaches to enhance data interpretation. The review underscores the role of interactive visual interfaces in improving the accessibility of large-scale food safety data and supporting decision-making processes.