Published on in Vol 24, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40449, first published .
Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study

Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study

Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study

Journals

  1. Bond A, Mccay K, Lal S. Artificial intelligence & clinical nutrition: What the future might have in store. Clinical Nutrition ESPEN 2023;57:542 View
  2. Ho D, Chiu W, Kao J, Tseng H, Yao C, Su H, Wei P, Le N, Nguyen H, Chang J. Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app. Nutrition 2023;116:112212 View
  3. Leino A, Magee J, Kershaw D, Pai M, Park J. A Comprehensive Mixed‐Method Approach to Characterize the Source of Diurnal Tacrolimus Exposure Variability in Children: Systematic Review, Meta‐analysis, and Application to an Existing Data Set. The Journal of Clinical Pharmacology 2024;64(3):334 View
  4. Larke J, Chin E, Bouzid Y, Nguyen T, Vainberg Y, Lee D, Pirsiavash H, Smilowitz J, Lemay D. Surveying Nutrient Assessment with Photographs of Meals (SNAPMe): A Benchmark Dataset of Food Photos for Dietary Assessment. Nutrients 2023;15(23):4972 View
  5. Khalifa M, Albadawy M. Artificial intelligence for diabetes: Enhancing prevention, diagnosis, and effective management. Computer Methods and Programs in Biomedicine Update 2024;5:100141 View
  6. Iglesies-Grau J, Dionne V, Latour É, Gayda M, Besnier F, Gagnon D, Debray A, Gagnon C, Pelletier V, Nigam A, L’Allier P, Juneau M, Bouabdallaoui N, Bherer L. Mediterranean diet and time-restricted eating as a cardiac rehabilitation approach for patients with coronary heart disease and pre-diabetes: the DIABEPIC-1 protocol of a feasibility trial. BMJ Open 2023;13(10):e073763 View
  7. Atwal K. Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence. Nutrition in Clinical Practice 2024;39(4):736 View
  8. Mauldin K, Pignotti G, Gieng J. Measures of nutrition status and health for weight‐inclusive patient care: A narrative review. Nutrition in Clinical Practice 2024;39(4):751 View
  9. Ford K, Quintanilha M, Trottier C, Wismer W, Sawyer M, Siervo M, Deutz N, Vallianatos H, Prado C. Exploring relationships with food after dietary intervention in patients with colorectal cancer: a qualitative analysis from the Protein Recommendations to Increase Muscle (PRIMe) trial. Supportive Care in Cancer 2024;32(7) View