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

New Methods (1145) Eating Disorders (104) Obesity and Nutrition as Public Health Problem (410) Instruments and Questionnaires for Nutrition and Food Intake (216) Innovations and Technology for Healthy Eating Education (495) Web-based and Mobile Health Interventions (4077) Prevention and Health Promotion (1398) Speech and Phonetics in Verbal Protocols (Think Aloud, Recall, and Explanation Tasks) (95)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48817, first published .
Dietary Intake Assessment Using a Novel, Generic Meal–Based Recall and a 24-Hour Recall: Comparison Study

Dietary Intake Assessment Using a Novel, Generic Meal–Based Recall and a 24-Hour Recall: Comparison Study

Dietary Intake Assessment Using a Novel, Generic Meal–Based Recall and a 24-Hour Recall: Comparison Study

Authors of this article:

Cathal O'Hara1, 2, 3 Author Orcid Image ;   Eileen R Gibney1, 2, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. O’Hara C, Kent G, Flynn A, Gibney E, Timon C. An Evaluation of ChatGPT for Nutrient Content Estimation from Meal Photographs. Nutrients 2025;17(4):607 View
  2. Gemesi K, Holzmann S, Böhm M, Leipold N, Hauptmann H, Lurz M, Groh G, Hauner H, Krcmar H, Holzapfel C. ‘The wisdom of crowds’: a survey on the rating of nutritional values of meals in digital pictures. BMJ Nutrition, Prevention & Health 2025;8(1):184 View

Conference Proceedings

  1. Kadari T, Maurya K, Sinha T. Proceedings of the 2025 9th International Conference on Medical and Health Informatics. NutriDetect, AI Nutrition Companion, Simplifying One Meal at a Time View