This paper is in the following e-collection/theme issue:

Digital Health Reviews (1326) Instruments and Questionnaires for Nutrition and Food Intake (169) Innovations and Technology for Healthy Eating Education (425) Artificial Intelligence (1421) Applications of AI (104) Obesity (87) mHealth for Data Collection and Research (981)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51432, first published .
Advancements in Using AI for Dietary Assessment Based on Food Images: Scoping Review

Advancements in Using AI for Dietary Assessment Based on Food Images: Scoping Review

Advancements in Using AI for Dietary Assessment Based on Food Images: Scoping Review

Authors of this article:

Phawinpon Chotwanvirat1, 2 Author Orcid Image ;   Aree Prachansuwan3 Author Orcid Image ;   Pimnapanut Sridonpai3 Author Orcid Image ;   Wantanee Kriengsinyos3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Phawinpon Chotwanvirat   1, 2 , PhD ;   Aree Prachansuwan   3 , PhD ;   Pimnapanut Sridonpai   3 , MSc ;   Wantanee Kriengsinyos   3 , PhD

1 Theptarin Diabetes, Thyroid, and Endocrine Center, Vimut-Theptarin Hospital, Bangkok, Thailand

2 Diabetes and Metabolic Care Center, Taksin Hospital, Medical Service Department, Bangkok Metropolitan Administration, Bangkok, Thailand

3 Human Nutrition Unit, Food and Nutrition Academic and Research Cluster, Institute of Nutrition, Mahidol University, Nakhon Pathom, Thailand

Corresponding Author:

  • Wantanee Kriengsinyos, PhD
  • Human Nutrition Unit, Food and Nutrition Academic and Research Cluster, Institute of Nutrition
  • Mahidol University
  • 999 Phutthamonthon 4 Rd., Salaya
  • Nakhon Pathom, 73170
  • Thailand
  • Phone: 66 2 800 2380
  • Fax: 66 2 441 9344
  • Email: wantanee.krieng@mahidol.ac.th