TY  - JOUR
AU  - Yang, Lin
AU  - Guo, Zhen
AU  - Xu, Xiaowei
AU  - Kang, Hongyu
AU  - Lai, Jianqiang
AU  - Li, Jiao
PY  - 2024
DA  - 2024/11/15
TI  - An Online Multimodal Food Data Exploration Platform for Specific Population Health: Development Study
JO  - JMIR Form Res
SP  - e55088
VL  - 8
KW  - Chinese food data
KW  - multimodal knowledge graph
KW  - online platform
KW  - population health promotion
KW  - health promotion
KW  - nutrients
KW  - diet
KW  - pregnant women
AB  - Background: Nutrient needs vary over the lifespan. Improving knowledge of both population groups and care providers can help with healthier food choices, thereby promoting population health and preventing diseases. Providing evidence-based food knowledge online is credible, low cost, and easily accessible. Objective: This study aimed to develop an online multimodal food data exploration platform for easy access to evidence-based diet- and nutrition-related data. Methods: We developed an online platform named Food Atlas in collaboration with a multidisciplinary expert group from the National Institute for Nutrition and Health and Peking Union Medical College Hospital in China. To demonstrate its feasibility for Chinese food for pregnant women, a user-friendly and high-quality multimodal food knowledge graph was constructed, and various interactions with graph-structured data were developed for easy access, including graph-based interactive visualizations, natural language retrieval, and image-text retrieval. Subsequently, we evaluated Food Atlas from both the system perspective and the user perspective. Results: The constructed multimodal food knowledge graph contained a total of 2011 entities, 10,410 triplets, and 23,497 images. Its schema consisted of 11 entity types and 26 types of semantic relations. Compared with 5 other online dietary platforms (Foodwake, Boohee, Xiachufang, Allrecipes, and Yummly), Food Atlas offers a distinct and comprehensive set of data content and system functions desired by target populations. Meanwhile, a total of 28 participants representing 4 different user groups were recruited to evaluate its usability: preparing for pregnancy (n=8), pregnant (n=12), clinicians (n=5), and dietitians (n=3). The mean System Usability Scale index of our platform was 82.5 (SD 9.94; range 40.0-82.5). This above-average usability score and the use cases indicated that Food Atlas is tailored to the needs of the target users. Furthermore, 96% (27/28) of the participants stated that the platform had high consistency, illustrating the necessity and effectiveness of health professionals participating in online, evidence-based resource development. Conclusions: This study demonstrates the development of an online multimodal food data exploration platform and its ability to meet the rising demand for accessible, credible, and appropriate evidence-based online dietary resources. Further research and broader implementation of such platforms have the potential to popularize knowledge, thereby helping populations at different life stages make healthier food choices. 
SN  - 2561-326X
UR  - https://formative.jmir.org/2024/1/e55088
UR  - https://doi.org/10.2196/55088
DO  - 10.2196/55088
ID  - info:doi/10.2196/55088
ER  -