AI-driven Personalized Dietary Predictor Design Study

Many of the technologies we routinely use already, such as search engines (e.g., Google), streaming music services (e.g., YouTube Music), video services (e.g., Netflix), and online shopping sites (e.g., Amazon), are already identifying the personal characteristics of humans and predicting what the personal want, along with the vast amount of data from others. The power of this big data is changing many areas of human life.

Is there anything as important as eating as a subject of research to maintain a healthy life? The human body consists of what we eat, but how well do we know what to eat? Or how well do you know what's right for you?

The concept of precision health care is being strengthened, with emphasis on 4P—prediction, prevention, personalization and participation. Already, the market is adopting big data and artificial intelligence technology to propose and supply food tailored to individuals. Now these services need to be verified through academic research and strong scientific evidences.

We are about to study the Agro-Nutrient-Health association through the extensive data extracted from literature, public databases, and PubMed using Natural Language Processing (NLP). The efforts to understand the food complexity (foodome) and the individual's genome, epi-genome, transcriptome, proteome, metabolome, microbiome, and exposome are undergoing. These big data enable us to identify the pharmacology of foodome and the physiological characteristics of individuals and distinguish between responders and non-responders to specific nutrients through machine learning and artificial intelligence (AI).

The AI-driven personalized dietary predictor we are trying to implement can be applied to the development of personalized sustainable agro-medical products—medicine, oriental medicine, supplements, cosmetic, diet, smart farms, etc. We are collaborating with leading bio-tech companies and working hard to raise money for the research to design the AI-driven personalized dietary predictor.

We are always working on future-oriented keywords, agriculture, planet, environment, anthropocene, sustainability, food, bio, convergence, health, personalization, big data, AI, etc. We would like to share relevant social issues and trends with various people through the hosting of symposiums and contribute to the popularization of related disciplines.

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Join us for the "Development of personalized diet prediction platform research"

(농림축산식품부 농림식품기술기획평가원) 맞춤형 식이 설계 플랫폼 개발 서울대학교 농업생명과학대학 식품바이오융합연구소는 "비영리기관"으로 "맞춤형 식이 설계 플랫폼 개발"을 위해 연구해 왔으며, 서울대학교 의료빅데이터 연구센터, 서울대학교 병원, 서울대학교 AI연구원과 함께 합니다. 현재 2월 22일까지 접수하는 농림축산식품부 농림식품기술기획평가원 2021년

YouTube : Immune Dining Table during the COVID-19 Era

코로나시대의 면역식탁. 정밀면역식이를 위한 나와 당신, 우리의 빅데이터 김 지 영 연구교수 서울대학교 식품바이오융합연구소 E-mail : 우리의 면역계는 매우 복잡하고, 특정 음식이나 영양소가 아닌 여러 요인에 의해 영향을 받는다. 균형 잡힌 식단, 적절한 수면

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