Titre :	Artificial Intelligence in Nutrition Analysis
Type de document :	texte imprimé
Auteurs :	Pravin Ghatge, Auteur
Editeur :	Burlington [Canada] : Delve Publishing
Année de publication :	2026
Importance :	1 vol. (433 p.)
Présentation :	ill., couv. ill. en coul.
Format :	PDF
ISBN/ISSN/EAN :	978-1-83441-369-3
Langues :	Français
Catégories :	Bibliothèque Numérique:Livre Electronique
Mots-clés :	- Artificial Intelligence - Nutrition Analysis - L'intelligence artificielle - l'analyse nutritionnelle
Index. décimale :	353.56 Alimentation et aliments
Résumé :	Artificial intelligence has revolutionized the field of nutrition science by enabling automated analysis of dietary patterns, nutrient estimation, and health prediction. Through data-driven insights, AI supports personalized nutrition and policy design. Artificial Intelligence in Nutrition Analysis explores the use of machine learning, image recognition, and natural language processing in dietary assessment. The book discusses AI-powered food tracking, nutrient profiling, and predictive analytics for health outcomes. It also examines ethical and data privacy concerns in digital nutrition tools. With examples from clinical and consumer applications, it offers a forward-looking view of how technology is transforming modern nutritional analysis.

Artificial Intelligence in Nutrition Analysis [texte imprimé] / Pravin Ghatge, Auteur . - Burlington (Canada) : Delve Publishing, 2026 . - 1 vol. (433 p.) : ill., couv. ill. en coul. ; PDF.
ISBN : 978-1-83441-369-3
Langues : Français

Catégories :	Bibliothèque Numérique:Livre Electronique
Mots-clés :	- Artificial Intelligence - Nutrition Analysis - L'intelligence artificielle - l'analyse nutritionnelle
Index. décimale :	353.56 Alimentation et aliments
Résumé :	Artificial intelligence has revolutionized the field of nutrition science by enabling automated analysis of dietary patterns, nutrient estimation, and health prediction. Through data-driven insights, AI supports personalized nutrition and policy design. Artificial Intelligence in Nutrition Analysis explores the use of machine learning, image recognition, and natural language processing in dietary assessment. The book discusses AI-powered food tracking, nutrient profiling, and predictive analytics for health outcomes. It also examines ethical and data privacy concerns in digital nutrition tools. With examples from clinical and consumer applications, it offers a forward-looking view of how technology is transforming modern nutritional analysis.