Published on in Vol 12 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45218, first published .
Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study

Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study

Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study

Journals

  1. Fujio K, Nagino K, Huang T, Sung J, Akasaki Y, Okumura Y, Midorikawa-Inomata A, Fujimoto K, Eguchi A, Miura M, Hurramhon S, Yee A, Hirosawa K, Ohno M, Morooka Y, Murakami A, Kobayashi H, Inomata T. Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis. Scientific Reports 2023;13(1) View
  2. Handayani A, Valentina C, Suryaningrum I, Megasafitri P, Juliari I, Pramita I, Nakayama S, Shimizu E, Triningrat A. Interobserver Reliability of Tear Break-Up Time Examination Using “Smart Eye Camera” in Indonesian Remote Area. Clinical Ophthalmology 2023;Volume 17:2097 View
  3. Zhang S, Echegoyen J. Design and Usability Study of a Point of Care mHealth App for Early Dry Eye Screening and Detection. Journal of Clinical Medicine 2023;12(20):6479 View
  4. Wolffsohn J. 2022 Glenn A. Fry Award lecture: Enhancing clinical assessment for improved ophthalmic management. Optometry and Vision Science 2024;101(1):12 View