Published on in Vol 22, No 5 (2020): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16658, first published .
Use of Smartphones to Detect Diabetic Retinopathy: Scoping Review and Meta-Analysis of Diagnostic Test Accuracy Studies

Use of Smartphones to Detect Diabetic Retinopathy: Scoping Review and Meta-Analysis of Diagnostic Test Accuracy Studies

Use of Smartphones to Detect Diabetic Retinopathy: Scoping Review and Meta-Analysis of Diagnostic Test Accuracy Studies

Journals

  1. Adlung L, Cohen Y, Mor U, Elinav E. Machine learning in clinical decision making. Med 2021;2(6):642 View
  2. Hyun M, Lee J, Ko S, Hwang J. Improving Glycemic Control in Type 2 Diabetes Using Mobile Applications and e-Coaching: A Mixed Treatment Comparison Network Meta-Analysis. Journal of Diabetes Science and Technology 2022;16(5):1239 View
  3. Jansen L, Shah P, Wabbels B, Holz F, Finger R, Wintergerst M. Learning curve evaluation upskilling retinal imaging using smartphones. Scientific Reports 2021;11(1) View
  4. Pieczynski J, Kuklo P, Grzybowski A. The Role of Telemedicine, In-Home Testing and Artificial Intelligence to Alleviate an Increasingly Burdened Healthcare System: Diabetic Retinopathy. Ophthalmology and Therapy 2021;10(3):445 View
  5. Fan K, Zhao Y. Mobile health technology: a novel tool in chronic disease management. Intelligent Medicine 2022;2(1):41 View
  6. Pujari A, Saluja G, Agarwal D, Sinha A, P R A, Kumar A, Sharma N. Clinical Role of Smartphone Fundus Imaging in Diabetic Retinopathy and Other Neuro-retinal Diseases. Current Eye Research 2021;46(11):1605 View
  7. Fernandes A, Ferraz A, Brant R, Malerbi F. Diabetic retinopathy screening and treatment through the Brazilian National Health Insurance. Scientific Reports 2022;12(1) View
  8. Attiku Y, He Y, Nittala M, Sadda S. Current status and future possibilities of retinal imaging in diabetic retinopathy care applicable to low- and medium-income countries. Indian Journal of Ophthalmology 2021;69(11):2968 View
  9. Shah D, Dewan L, Singh A, Jain D, Damani T, Pandit R, Porwal A, Bhatnagar S, Shrishrimal M, Patel A. Utility of a smartphone assisted direct ophthalmoscope camera for a general practitioner in screening of diabetic retinopathy at a primary health care center. Indian Journal of Ophthalmology 2021;69(11):3144 View
  10. Qader A, Er H, Sow C. The effectiveness of smartphone ophthalmoscope compared to direct ophthalmoscope as a teaching tool. The Asia Pacific Scholar 2022;7(4):22 View
  11. Vieira M, Fernandes R, Ambrósio A, Cardoso V, Carvalho M, Weng Kung P, Neves M, Mendes Pinto I. Lab-on-a-chip technologies for minimally invasive molecular sensing of diabetic retinopathy. Lab on a Chip 2022;22(10):1876 View
  12. Nanegrungsunk O, Patikulsila D, Sadda S. Ophthalmic imaging in diabetic retinopathy: A review. Clinical & Experimental Ophthalmology 2022;50(9):1082 View
  13. Salongcay R, Aquino L, Salva C, Saunar A, Alog G, Sun J, Peto T, Silva P. Comparison of Handheld Retinal Imaging with ETDRS 7-Standard Field Photography for Diabetic Retinopathy and Diabetic Macular Edema. Ophthalmology Retina 2022;6(7):548 View
  14. Sobue M, Takata H, Takehara H, Haruta M, Tashiro H, Sasagawa K, Kawasaki R, Ohta J. Clear Fundus Images Through High-Speed Tracking Using Glare-Free IR Color Technology. Journal of Robotics and Mechatronics 2022;34(5):1152 View
  15. Takehara H, Wang Z, Tang H, Kishida N, Horiki Y, Sobue M, Haruta M, Tashiro H, Sasagawa K, Ohta J. [Invited Paper] Near-infrared Colorized Imaging Technologies and Their Fundus Camera Applications. ITE Transactions on Media Technology and Applications 2022;10(2):59 View
  16. Ma J, Cao N. An Analysis of the Interaction between Ancient Literature Informatization Project and Classical Literature Research Based on Intelligent Computing. Mathematical Problems in Engineering 2022;2022:1 View
  17. Yao X, Son T, Ma J. Developing portable widefield fundus camera for teleophthalmology: Technical challenges and potential solutions. Experimental Biology and Medicine 2022;247(4):289 View
  18. Bortoli J, Silber P, Picetti E, Silva C, Pakter H. Retinografia como forma de rastreio de retinopatia diabética em hospital terciário do Sistema Único de Saúde. Revista Brasileira de Oftalmologia 2022;81 View
  19. Jabir A, Zaheer H, Zaheer M, Zaheer E, Birdsong R. Detection and Diagnosis of Retinoblastoma: Can Mobile Devices Be the Next Step Toward Early Intervention?. Cureus 2022 View
  20. Ahmed A, Aziz S, Abd-alrazaq A, Farooq F, Sheikh J. Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review. Journal of Medical Internet Research 2022;24(8):e36010 View
  21. Ramasamy K, Mishra C, Kannan N, Namperumalsamy P, Sen S. Telemedicine in diabetic retinopathy screening in India. Indian Journal of Ophthalmology 2021;69(11):2977 View
  22. Nakayama L, Ribeiro L, Malerbi F, Regatieri C. Ophthalmology and Artificial Intelligence: Present or Future? A Diabetic Retinopathy Screening Perspective of the Pursuit for Fairness. Frontiers in Ophthalmology 2022;2 View
  23. Rêgo S, Monteiro-Soares M, Dutra-Medeiros M, Soares F, Dias C, Nunes F. Implementation and Evaluation of a Mobile Retinal Image Acquisition System for Screening Diabetic Retinopathy: Study Protocol. Diabetology 2022;3(1):1 View
  24. Biran A, Loewenstein A, Mezad-Koursh D, Iglicki M, Zur D. Ophthalmic Telemedicine in the Pandemic–Endemic World: Present and Future Perspectives. US Ophthalmic Review 2022;16(1):17 View
  25. Alexopoulos P, Madu C, Wollstein G, Schuman J. The Development and Clinical Application of Innovative Optical Ophthalmic Imaging Techniques. Frontiers in Medicine 2022;9 View
  26. Omari A, Samad M, Bakhsh S, Tajran J, Williams G. Accuracy of Remote Diagnosis of Acute Posterior Segment Pathology by Residents and Attendings Captured with a Smartphone and Standard 20/28D Lens. Clinical Ophthalmology 2022;Volume 16:2751 View
  27. Zhu C, Zhu J, Wang L, Xiong S, Zou Y, Huang J, Xie H, Zhang W, Wu H, Liu Y. Development and validation of a risk prediction model for diabetic retinopathy in type 2 diabetic patients. Scientific Reports 2023;13(1) View
  28. Masson A, Villard F, Finger M, DeGottrau P, Gaillard M. Utilisation du smartphone dans la sémiologie clinique de la dystrophie épithéliale de Cogan. Klinische Monatsblätter für Augenheilkunde 2023;240(04):603 View
  29. Ummah F, Rosida L, Putri A. Breastfeeding Education: A Scoping Review. Malaysian Journal of Medicine and Health Sciences 2023;19(2):293 View
  30. Bouchi R, Sugiyama T, Goto A, Ohsugi M, Yoshioka N, Katagiri H, Mita T, Hirota Y, Ikegami H, Matsuhisa M, Araki E, Yokoyama H, Minami M, Yamazaki K, Jinnouchi H, Ikeda H, Fujii H, Nogawa M, Kaneshige M, Miyo K, Ueki K. Impact of COVID‐19 pandemic on behavioral changes and glycemic control and a survey of telemedicine in patients with diabetes: A multicenter retrospective observational study. Journal of Diabetes Investigation 2023;14(8):994 View
  31. Venkatesh K, Brito G. Lessons on regulation and implementation from the first FDA-cleared autonomous AI - Interview with Chairman and Founder of Digital Diagnostics Michael Abramoff. Healthcare 2023;11(2):100692 View
  32. Owusu-Afriyie B, Gende T, Tapilas M, Zimbare N, Kewande J. Patients’ Perspective on Barriers to Utilization of a Diabetic Retinopathy Screening Service. Diabetology 2023;4(3):393 View
  33. Pelayes D, Cotic M, Folgar A. Inteligencia Artificial. Una Nueva Frontera en el Diagnóstico de la Retinopatía Diabética. Highlights of Vitreoretina 2023;16(3):21 View
  34. Vilela M, Arrigo A, Parodi M, da Silva Mengue C. Smartphone Eye Examination: Artificial Intelligence and Telemedicine. Telemedicine and e-Health 2024;30(2):341 View
  35. Yang K, Lu Y, Xue L, Yang Y, Chang S, Zhou C. URNet: System for recommending referrals for community screening of diabetic retinopathy based on deep learning. Experimental Biology and Medicine 2023;248(11):909 View
  36. Prayogo M, Zaharo A, Damayanti N, Widyaputri F, Thobari J, Susanti V, Sasongko M. Accuracy of Low-Cost, Smartphone-Based Retinal Photography for Diabetic Retinopathy Screening: A Systematic Review. Clinical Ophthalmology 2023;Volume 17:2459 View
  37. Che Mohamad Nor A, Mohd Zain Z, Ahmad Noorden M. Application and Modification of RT-LAMP for Rapid Detection of SARS-CoV-2 Viral Genome. Malaysian Journal of Medicine and Health Sciences 2023;19(2):286 View
  38. Saoud O. Retrospective study of patients with rhegmatogenous retinal detachments and high complicated myopia. Experimental and Clinical Medicine 2023;92(2):22 View
  39. Tomić M, Vrabec R, Hendelja Đ, Kolarić V, Bulum T, Rahelić D. Diagnostic Accuracy of Hand-Held Fundus Camera and Artificial Intelligence in Diabetic Retinopathy Screening. Biomedicines 2023;12(1):34 View
  40. Song A, Borkar D. Advances in Teleophthalmology Screening for Diabetic Retinopathy. International Ophthalmology Clinics 2024;64(1):97 View
  41. Zhang J, Luo X, Li D, Peng Y, Gao G, Lei L, Gao M, Lu L, Xu Y, Yu T, Lin S, Ma Y, Yao C, Zou H. Evaluating imaging repeatability of fully self-service fundus photography within a community-based eye disease screening setting. BioMedical Engineering OnLine 2024;23(1) View
  42. Nursalamah M, Karfiati F, Ratnaningsih N, Widihastha S. Efficacy of Smartphone-based Fundus Photo in Vision Threatening Diabetic Retinopathy Screening: Developing Country Perspective. The Open Ophthalmology Journal 2024;18(1) View
  43. Yao J, Lim J, Lim G, Ong J, Ke Y, Tan T, Tan T, Vujosevic S, Ting D. Novel artificial intelligence algorithms for diabetic retinopathy and diabetic macular edema. Eye and Vision 2024;11(1) View
  44. Zhang Z, Deng C, Paulus Y. Advances in Structural and Functional Retinal Imaging and Biomarkers for Early Detection of Diabetic Retinopathy. Biomedicines 2024;12(7):1405 View
  45. Shahzad R, Mehmood A, Shabbir D, Siddiqui M, Nakayama L. Diagnostic accuracy of a smartphone-based device (VistaView) for detection of diabetic retinopathy: A prospective study. PLOS Digital Health 2024;3(11):e0000649 View
  46. Romero-Aroca P, Fontoba-Poveda B, Garcia-Curto E, Valls A, Cristiano J, Llagostera-Serra M, Morente-Lorenzo C, Mendez-Marín I, Baget-Bernaldiz M. Two Handheld Retinograph Devices Evaluated by Ophthalmologists and an Artificial Intelligence Algorithm. Journal of Clinical Medicine 2024;13(22):6935 View
  47. Green G, Flores R, Figueroa E, Kuo T, Daskivich L. Assessing the Feasibility of Handheld Cameras to Increase Access to Teleretinal Diabetic Retinopathy Screenings in Safety Net Clinics in Los Angeles. Diabetology 2024;5(6):629 View

Books/Policy Documents

  1. Kavitha S, Raju S, Karumanchi V, Rao D, Rajeswari T. Sustainable Communication Networks and Application. View
  2. Yuen J, Pike S, Khachikyan S, Nallasamy S. Digital Health. View
  3. Piyasena P, Peto T, Congdon N. Digital Eye Care and Teleophthalmology. View
  4. Dhiviya Rose J, Jain A, Tiwari S. Machine Intelligence for Research and Innovations. View
  5. Chebly K, Varnum C. Leading an Academic Medical Practice. View