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

mHealth for Screening (294) Ophthalmology (66) Health Services in Resource-Poor Settings and LMICs (527) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (706) School-based Health Education and Interventions (113) Screening and Early Diagnosis in Pediatrics (41)

Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18226, first published .
A One-Step, Streamlined Children’s Vision Screening Solution Based on Smartphone Imaging for Resource-Limited Areas: Design and Preliminary Field Evaluation

A One-Step, Streamlined Children’s Vision Screening Solution Based on Smartphone Imaging for Resource-Limited Areas: Design and Preliminary Field Evaluation

A One-Step, Streamlined Children’s Vision Screening Solution Based on Smartphone Imaging for Resource-Limited Areas: Design and Preliminary Field Evaluation

Authors of this article:

Shuoxin Ma1, 2 Author Orcid Image ;   Yongqing Guan3 Author Orcid Image ;   Yazhen Yuan3 Author Orcid Image ;   Yuan Tai2 Author Orcid Image ;   Tan Wang2 Author Orcid Image
Article Authors Cited by (23) Tweetations (1) Metrics

Journals

  1. Oke I, VanderVeen D. Machine Learning Applications in Pediatric Ophthalmology. Seminars in Ophthalmology 2021;36(4):210 View
  2. Wang X, Yang Y, Wu Y, Wei W, Dong L, Li Y, Tan X, Cao H, Zhang H, Ma X, Jiang Q, Zhou Y, Yang W, Li C, Gu Y, Ding L, Qin Y, Chen Q, Li L, Lian M, Ma J, Cui D, Huang Y, Liu W, Yang X, Yu S, Chen J, Wang D, Lin Z, Yan P, Lin H. The national multi-center artificial intelligent myopia prevention and control project. Intelligent Medicine 2021;1(2):51 View
  3. Tenório Albuquerque Madruga Mesquita M, Azevedo Valente T, de Almeida J, Meireles Teixeira J, Cord Medina F, dos Santos A. A mhealth application for automated detection and diagnosis of strabismus. International Journal of Medical Informatics 2021;153:104527 View
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  7. 吴 逸. Research on Intelligent Fitting Method of Orthokeratology Lens Based on Improved Resnet50. Software Engineering and Applications 2023;12(06):832 View
  8. Csizek Z, Mikó-Baráth E, Budai A, Frigyik A, Pusztai Á, Nemes V, Závori L, Fülöp D, Czigler A, Szabó-Guth K, Buzás P, Piñero D, Jandó G. Artificial intelligence-based screening for amblyopia and its risk factors: comparison with four classic stereovision tests. Frontiers in Medicine 2023;10 View
  9. Jin K, Li Y, Wu H, Tham Y, Koh V, Zhao Y, Kawasaki R, Grzybowski A, Ye J. Integration of smartphone technology and artificial intelligence for advanced ophthalmic care: A systematic review. Advances in Ophthalmology Practice and Research 2024;4(3):120 View
  10. Wong D, Alsaif A, Bender L. The Role of Telemedicine in Strabismus Assessment: A Narrative Review and Meta-Analysis. Telemedicine and e-Health 2024;30(8):e2240 View
  11. Wu D, Li Y, Zhang H, Yang X, Mao Y, Chen B, Feng Y, Chen L, Zou X, Nie Y, Yin T, Yang Z, Liu J, Shang W, Yang G, Liu L. An artificial intelligence platform for the screening and managing of strabismus. Eye 2024;38(16):3101 View
  12. Liu M, Wu X, Li Z, Tan D, Huang C. Assessment of Eye Care Apps for Children and Adolescents Based on the Mobile App Rating Scale: Content Analysis and Quality Assessment. JMIR mHealth and uHealth 2024;12:e53805 View
  13. Wu D, Huang X, Chen L, Hou P, Liu L, Yang G. Integrating artificial intelligence in strabismus management: current research landscape and future directions. Experimental Biology and Medicine 2024;249 View
  14. Vijendran S, Alok Y, Kuzhuppilly N, Bhat J, Kamath Y. Effectiveness of smartphone technology for detection of paediatric ocular diseases—a systematic review. BMC Ophthalmology 2025;25(1) View
  15. Zug M, Geisler D, Meyer L, Faucher L, Sauer A. L’intelligence artificielle appliquée à la prise en charge du strabisme : revue de la littérature. Revue Francophone d'Orthoptie 2025 View
  16. Syauqie M, Hastono S, Siregar K, Farieda Moeloek N. Revealing the inherent properties of pupillary red reflex in refractive errors by smartphone imaging: a study in Indonesia's population. Optics Continuum 2025;4(7):1519 View
  17. Zhang Z, Lv L, Chen D, Chen Y, Zhang W, Li F, Zhou J. Shaping the future of myopia with artificial intelligence: Mapping trends and promising directions. Advances in Ophthalmology Practice and Research 2025;5(4):245 View
  18. Syauqie M, Patria H, Hastono S, Siregar K, Moeloek N. Deep learning for vision screening in resource-limited settings: development of multi-branch CNN for refractive error detection based on smartphone image. Frontiers in Computer Science 2025;7 View
  19. Rodriguez D, Rivera Gomez A, Serrezuela R. Development of an embedded diagnostic tool for visual misalignment screening. HardwareX 2025;23:e00692 View
  20. Sultan Fahad N Althunayan , Bdulrahman ASIRI , Moath Badr Hassan SOBAIH , Talhah Mohammed ALGHASHAM , Nouf Sulaiman Masad ALBALAWİ , Abdullah Hammad A ALSADOON , Mısharı Abdulrahman ALSUBAIHI , Haitham Mohammed Ali ALHAZMI , Basem Ali Sulaiman WASEL . The Feasibility of Using a Handheld Auto-refractor as a Tool for Vision Screening in Pediatric Primary Care to Detect Amblyogenic Risk Factors. International Journal of Computational and Experimental Science and Engineering 2025;11(3) View
  21. Wang R, Lyu J, Yang Y, Bi S, Yu H, Deng H, Han M, Ma W, Wan M, Peng S, Yu X, Xu F, Lin H. A Smartphone-Based Digital Ruler to Automatically Measure Strabismus in Ophthalmologist-Level: A Prospective, Multicenter Cohort Study. NEJM AI 2025;2(11) View

Books/Policy Documents

  1. Hashimoto R, Waldman C. Contemporary Issues in Global Medicine and Moving Toward International Healthcare Equity. View

Conference Proceedings

  1. Wang T, Jin M, Xu C, Liu Z, Wang X. 2024 3rd International Conference on Health Big Data and Intelligent Healthcare (ICHIH). Mobile Strabismus Automatic Detection Method Combining Alternating Cover Test and Deep Learning View