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

Assisted Living for the Elderly and Nursing Home Care (187) Artificial Intelligence (1735) Instruments and Questionnaires for Nutrition and Food Intake (185) Food Sciences and Nutrition Engineering (55) mHealth for Wellness, Behavior Change and Prevention (3099)

Published on in Vol 5, No 4 (2022): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37590, first published .
Enhancing Food Intake Tracking in Long-term Care With Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology: Validation and Feasibility Assessment

Enhancing Food Intake Tracking in Long-term Care With Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology: Validation and Feasibility Assessment

Enhancing Food Intake Tracking in Long-term Care With Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology: Validation and Feasibility Assessment

Authors of this article:

Kaylen Pfisterer1, 2, 3, 4 Author Orcid Image ;   Robert Amelard3, 5 Author Orcid Image ;   Jennifer Boger1, 3, 5 Author Orcid Image ;   Heather Keller3, 6 Author Orcid Image ;   Audrey Chung1, 2 Author Orcid Image ;   Alexander Wong1, 2, 3 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Ase A, Borowicz J, Rakocy K, Krzych-Fałta E, Samoliński B. Demographic and Physical Determinants of Unhealthy Food Consumption in Polish Long-Term Care Facilities. Nutrients 2025;17(6):1008 View

Conference Proceedings

  1. Rodríguez-de-Vera J, Estepa I, Bolaños M, Nagarajan B, Radeva P. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). LOFI: LOng-tailed FIne-Grained Network for Food Recognition View