| Titre : | Artificial intelligence in food science and nutrition: a narrative review (2022) |
| Auteurs : | Taiki Miyazawa ; Yoichi Hiratsuka ; Masako Toda ; Nozomu Hatakeyama ; Hitoshi Ozawa ; Chizumi Abe ; Ting-Yu Cheng ; Yuji Matsushima ; Yoshifumi Miyawaki ; Kinya Ashida ; Jun Iimura ; Tomohiro Tsuda ; Hiroto Bushita ; Kazuichi Tomonobu ; Satoshi Ohta ; Hsuan Chung ; Yusuke Omae ; Takayuki Yamamoto ; Makoto Morinaga ; Hiroshi Ochi ; Hajime Nakada ; Kazuhiro Otsuka ; Teruo Miyazawa |
| Type de document : | Article |
| Dans : | Nutrition reviews (Vol. 80, n° 12, December 2022) |
| Article en page(s) : | p. 2288-2300 |
| Note générale : | https://doi.org/10.1093/nutrit/nuac033 |
| Langues: | Anglais |
| Descripteurs : |
HE Vinci Apprentissage machine ; Apprentissage profond ; Chronologie ; Humains ; Intelligence artificielle (IA) ; Microbiome gastro-intestinal ; Nutriments ; Prestations des soins de santé ; Technologie alimentaire ; Toxicité |
| Résumé : | In the late 2010s, artificial intelligence (AI) technologies became complementary to the research areas of food science and nutrition. This review aims to summarize these technological advances by systematically describing the following: the use of AI in other fields (eg, engineering, pharmacy, and medicine); the history of AI in relation to food science and nutrition; the AI technologies currently used in the agricultural and food industries; and some of the important applications of AI in areas such as immunity-boosting foods, dietary assessment, gut microbiome profile analysis, and toxicity prediction of food ingredients. These applications are likely to be in great demand in the near future. This review can provide a starting point for brainstorming and for generating new AI applications in food science and nutrition that have yet to be imagined. |
| Disponible en ligne : | Oui |
| En ligne : | https://login.ezproxy.vinci.be/login?url=https://academic.oup.com/nutritionreviews/article/80/12/2288/6594763 |
Bibliothèques HE Vinci
