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

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
  4. Ambrosino C, Dai X, Antonio Aguirre B, Collins M. Pediatric and School-Age Vision Screening in the United States: Rationale, Components, and Future Directions. Children 2023;10(3):490 View
  5. Susanto A, Winarto H, Fahira A, Abdurrohman H, Muharram A, Widitha U, Warman Efirianti G, Eduard George Y, Tjoa K. Building an artificial intelligence-powered medical image recognition smartphone application: What medical practitioners need to know. Informatics in Medicine Unlocked 2022;32:101017 View
  6. Linde G, Chalakkal R, Zhou L, Huang J, O’Keeffe B, Shah D, Davidson S, Hong S. Automatic Refractive Error Estimation Using Deep Learning-Based Analysis of Red Reflex Images. Diagnostics 2023;13(17):2810 View
  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

Books/Policy Documents

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