An End-to-End Semantic Platform for Nutritional Diseases Management.

摘要: The self-management of nutritional diseases requires a system that combines food tracking with the potential risks categories on people’s health based their personal records (PHRs). challenges range from design an effective image classification strategy to development full-fledged knowledge-based system. This maps results into semantic information can be exploited for reasoning. However, current works mainly address single separately without integration whole pipeline. In this paper, we propose new end-to-end platform where: (i) aims extract pictures; (ii) ontology is used detecting risk factors specific diseases; (iii) Linked Open Data (LOD) Cloud queried extracting concerning related and comorbidities; and, (iv) users’ PHRs are generating proper feedback. Experiments conducted publicly released dataset. Quantitative qualitative evaluations, two living labs, demonstrate effectiveness suitability proposed approach.