%0 Journal Article
%@ 2561-326X
%I JMIR Publications
%V 8
%N 
%P e55088
%T An Online Multimodal Food Data Exploration Platform for Specific Population Health: Development Study
%A Yang,Lin
%A Guo,Zhen
%A Xu,Xiaowei
%A Kang,Hongyu
%A Lai,Jianqiang
%A Li,Jiao
%+ Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, No. 3, Yabao Rd, Chaoyang District, Beijing, 100020, China, 86 18618461596, li.jiao@imicams.ac.cn
%K Chinese food data
%K multimodal knowledge graph
%K online platform
%K population health promotion
%K health promotion
%K nutrients
%K diet
%K pregnant women
%D 2024
%7 15.11.2024
%9 Original Paper
%J JMIR Form Res
%G English
%X 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. 
%R 10.2196/55088
%U https://formative.jmir.org/2024/1/e55088
%U https://doi.org/10.2196/55088