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

mHealth for Wellness, Behavior Change and Prevention (2872) mHealth for Data Collection and Research (955) Instruments and Questionnaires for Nutrition and Food Intake (166)

Published on in Vol 7, No 2 (2019): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10931, first published .
Evaluating Mobile Health Apps for Customized Dietary Recording for Young Adults and Seniors: Randomized Controlled Trial

Evaluating Mobile Health Apps for Customized Dietary Recording for Young Adults and Seniors: Randomized Controlled Trial

Evaluating Mobile Health Apps for Customized Dietary Recording for Young Adults and Seniors: Randomized Controlled Trial

Authors of this article:

Ying-Chieh Liu1, 2 Author Orcid Image ;   Chien-Hung Chen3 Author Orcid Image ;   Ya-Chi Tsou1 Author Orcid Image ;   Yu-Sheng Lin2 Author Orcid Image ;   Hsin-Yun Chen4 Author Orcid Image ;   Jou-Yin Yeh5 Author Orcid Image ;   Sherry Yueh-Hsia Chiu5, 6 Author Orcid Image
Article Authors Cited by (12) Tweetations Metrics

Journals

  1. Liu Y, Wu S, Lin S, Chen C, Lin Y, Chen H. Usability of Food Size Aids in Mobile Dietary Reporting Apps for Young Adults: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(4):e14543 View
  2. Koepp J, Baron M, Hernandes Martins P, Brandenburg C, Kira A, Trindade V, Ley Dominguez L, Carneiro M, Frozza R, Possuelo L, De Mello Pinto M, Mahlmann Kipper L, Pinheiro da Costa B. The Quality of Mobile Apps Used for the Identification of Pressure Ulcers in Adults: Systematic Survey and Review of Apps in App Stores. JMIR mHealth and uHealth 2020;8(6):e14266 View
  3. Cajamarca G, Herskovic V, Rossel P. Enabling Older Adults’ Health Self-Management through Self-Report and Visualization—A Systematic Literature Review. Sensors 2020;20(15):4348 View
  4. Liu Y, Chen C, Lin Y, Chen H, Irianti D, Jen T, Yeh J, Chiu S. Design and Usability Evaluation of Mobile Voice-Added Food Reporting for Elderly People: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(9):e20317 View
  5. Surendran S, Lim C, Koh G, Yew T, Tai E, Foong P. Women’s Usage Behavior and Perceived Usefulness with Using a Mobile Health Application for Gestational Diabetes Mellitus: Mixed-Methods Study. International Journal of Environmental Research and Public Health 2021;18(12):6670 View
  6. Guo X, Pan T, Guo S. Socialized care services for the aged population: System construction and support measures. Frontiers of Engineering Management 2023;10(2):339 View
  7. Yang A, Singh N, Varshney U. Mobile Health Interventions and RCTs: Structured Taxonomy and Research Framework. Journal of Medical Systems 2022;46(10) View
  8. Wang Q, Liu J, Zhou L, Tian J, Chen X, Zhang W, Wang H, Zhou W, Gao Y. Usability evaluation of mHealth apps for elderly individuals: a scoping review. BMC Medical Informatics and Decision Making 2022;22(1) View
  9. Thornton L, Osman B, Champion K, Green O, Wescott A, Gardner L, Stewart C, Visontay R, Whife J, Parmenter B, Birrell L, Bryant Z, Chapman C, Lubans D, Slade T, Torous J, Teesson M, Van de Ven P. Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review. JMIR mHealth and uHealth 2022;10(2):e27337 View
  10. Liu Y, Onthoni D, Mohapatra S, Irianti D, Sahoo P. Deep-Learning-Assisted Multi-Dish Food Recognition Application for Dietary Intake Reporting. Electronics 2022;11(10):1626 View
  11. Garcia Reyes E, Kelly R, Buchanan G, Waycott J. Understanding Older Adults’ Experiences With Technologies for Health Self-management: Interview Study. JMIR Aging 2023;6:e43197 View
  12. Veena N, Prasad M, Aruna Deepthi S, Swaroopa Rani B, Nayak M, Someshwar S. An Optimized Recurrent Neural Network for re-modernize food dining bowls and estimating food capacity from images. Entertainment Computing 2024;50:100664 View