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projectThis platform provides health functional food data analysis and personalized health management features, supporting consumers in making safer and more effective choices.
Despite the rapid growth of the health functional food market, consumers are not provided with sufficient information regarding potential interactions between these products and medicines, nor the proper methods of consumption. Furthermore, the lack of recommendation systems tailored to individual health conditions increases the risk of side effects from indiscriminate intake.
This project utilizes Natural Language Processing (NLP) to standardize health functional food data. By providing personalized healthcare solutions, we aim to support the safe and informed use of health functional foods.
This platform provides health functional food data analysis and personalized health management features, supporting consumers in making safer and more effective choices. By utilizing Natural Language Processing (NLP)—an AI technology that enables computers to understand and process human language—the platform collects and analyzes public and private data to establish a structured database. This system automatically classifies ingredients, functionality, and intake methods while significantly enhancing search capabilities. In particular, the integration of the Ministry of Food and Drug Safety (MFDS) data with the pharmaceutical and disease databases from the developer, Ones Global, allows for a systematic analysis of interactions between health functional foods and medicines, providing highly precise and customized health information. Furthermore, the platform develops personalized recommendation algorithms that reflect a user’s health status, current medications, and lifestyle habits, proactively preventing potential side effects by analyzing interaction risks.
Through this platform, consumers can make safer and more effective selections of health functional foods, while the provision of interaction data between these products and medicines helps prevent adverse side effects. Furthermore, by offering precise health management solutions that leverage the convergence of public and private data, the platform will significantly improve the quality of personalized healthcare services.
| Before (AS-IS) | After (TO-BE) |
|---|---|
| The rise in adverse event reports and overseas direct purchases of health functional foods necessitates personalized recommendation services. | Diversification of access paths, nutrient recommendations based on user variable data, provision of evidence for nutrient recommendations, and provision of product information. |
Launch year: 2024
Case study courtesy of the National Information Society Agency, Republic of Korea, Apolitical's Content Partner. Sourced from Use Cases of Public AI Service, Vol.2, https://eng.nia.or.kr/site/nia_eng/ex/bbs/View.do?cbIdx=31975&bcIdx=29182&parentSeq=29210
In partnership with
National Information Society Agency (NIA)
In partnership with
National Information Society Agency (NIA)
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