Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41624, first published .
Artificial Intelligence in Community-Based Diabetic Retinopathy Telemedicine Screening in Urban China: Cost-effectiveness and Cost-Utility Analyses With Real-world Data

Artificial Intelligence in Community-Based Diabetic Retinopathy Telemedicine Screening in Urban China: Cost-effectiveness and Cost-Utility Analyses With Real-world Data

Artificial Intelligence in Community-Based Diabetic Retinopathy Telemedicine Screening in Urban China: Cost-effectiveness and Cost-Utility Analyses With Real-world Data

Journals

  1. Rizvi A, Rizvi F, Lalakia P, Hyman L, Frasso R, Sztandera L, Das A. Is Artificial Intelligence the Cost-Saving Lens to Diabetic Retinopathy Screening in Low- and Middle-Income Countries?. Cureus 2023 View
  2. Rajesh A, Davidson O, Lee C, Lee A. Artificial Intelligence and Diabetic Retinopathy: AI Framework, Prospective Studies, Head-to-head Validation, and Cost-effectiveness. Diabetes Care 2023;46(10):1728 View
  3. Wang Y, Liu C, Hu W, Luo L, Shi D, Zhang J, Yin Q, Zhang L, Han X, He M. Economic evaluation for medical artificial intelligence: accuracy vs. cost-effectiveness in a diabetic retinopathy screening case. npj Digital Medicine 2024;7(1) View
  4. Ramoutar R. An Economic Analysis for the Use of Artificial Intelligence in Screening for Diabetic Retinopathy in Trinidad and Tobago. Cureus 2024 View
  5. Wu H, Jin K, Yip C, Koh V, Ye J. A systematic review of economic evaluation of artificial intelligence-based screening for eye diseases: From possibility to reality. Survey of Ophthalmology 2024;69(4):499 View
  6. Zhang J, Lin S, Cheng T, Xu Y, Lu L, He J, Yu T, Peng Y, Zhang Y, Zou H, Ma Y. RETFound-enhanced community-based fundus disease screening: real-world evidence and decision curve analysis. npj Digital Medicine 2024;7(1) View
  7. Melo G, Nakayama L, Cardoso V, dos Santos L, Malerbi F. Synchronous Diagnosis of Diabetic Retinopathy by a Handheld Retinal Camera, Artificial Intelligence, and Simultaneous Specialist Confirmation. Ophthalmology Retina 2024;8(11):1083 View
  8. Karabeg M, Petrovski G, Hertzberg S, Erke M, Fosmark D, Russell G, Moe M, Volke V, Raudonis V, Verkauskiene R, Sokolovska J, Haugen I, Petrovski B. A pilot cost-analysis study comparing AI-based EyeArt® and ophthalmologist assessment of diabetic retinopathy in minority women in Oslo, Norway. International Journal of Retina and Vitreous 2024;10(1) View
  9. Kastrup N, Holst-Kristensen A, Valentin J. Landscape and challenges in economic evaluations of artificial intelligence in healthcare: a systematic review of methodology. BMC Digital Health 2024;2(1) View
  10. Quan H, Wang H, Yang Y, Yu H. The Safety and Effectiveness of Telemedicine for Cancer-Related Colostomy Care in the Early Stage of Discharge: A Prospective, Randomized, Single-Center Study. Telemedicine Reports 2024;5(1):212 View
  11. Zhang J, Xiao F, Zou H, Feng R, He J. Self-supervised learning-enhanced deep learning method for identifying myopic maculopathy in high myopia patients. iScience 2024;27(8):110566 View
  12. Injante R, Julca M. Detection of diabetic retinopathy using artificial intelligence: an exploratory systematic review. LatIA 2024;2:112 View
  13. Alay D. Uzaktan Sağlık Hizmetlerinin Ekonomik Değerlendirmesinin Sistematik Analizi: Diyabetik Retinopati Örneği. Arşiv Kaynak Tarama Dergisi 2024;33(3):172 View
  14. Lin S, Ma Y, Li L, Jiang Y, Peng Y, Yu T, Qian D, Xu Y, Lu L, Chen Y, Zou H. Cost-effectiveness and cost-utility of community-based blinding fundus diseases screening with artificial intelligence: A modelling study from Shanghai, China. Computers in Biology and Medicine 2024;183:109329 View

Books/Policy Documents

  1. Jagtap R, Bayrakdar S, Orhan K. Artificial Intelligence in Dentistry. View