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

Public Health Informatics (80) Diabetic Retinopathy (8) Artificial Intelligence (1216) Cost-Effectiveness and Economics (234) Telehealth and Telemonitoring (1575) Telemedicine for Diabetes (88)

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

Authors of this article:

Senlin Lin1, 2 Author Orcid Image ;   Yingyan Ma1, 2 Author Orcid Image ;   Yi Xu1, 2 Author Orcid Image ;   Lina Lu1, 2 Author Orcid Image ;   Jiangnan He1, 2 Author Orcid Image ;   Jianfeng Zhu1, 2 Author Orcid Image ;   Yajun Peng1, 2 Author Orcid Image ;   Tao Yu1, 2 Author Orcid Image ;   Nathan Congdon3, 4, 5 Author Orcid Image ;   Haidong Zou1, 2 Author Orcid Image
Article Authors Cited by (11) Tweetations (3) Metrics

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 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

Books/Policy Documents

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