Explore our sister journals here.

Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Published on 30.10.14 in Vol 16, No 10 (2014): October

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

Works citing "Rapid Grading of Fundus Photographs for Diabetic Retinopathy Using Crowdsourcing"

Christopher J Brady, Andrea C Villanti, Jennifer L Pearson, Thomas R Kirchner, Omesh P Gupta, Chirag P Shah

J Med Internet Res 2014 (Oct 30); 16(10):e233 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.3807):

(note that this is only a small subset of citations)

  1. Bouenizabila , Krempf M. Le numérique et l’Afrique : le pari gagnant pour la santé de demain ?: Exemple du dépistage de la rétinopathie diabétique. Médecine des Maladies Métaboliques 2018;12(7):595
    CrossRef
  2. . Applications of crowdsourcing in health: an overview. Journal of Global Health 2018;8(1)
    CrossRef
  3. Vedula SS, Malpani A, Ahmidi N, Khudanpur S, Hager G, Chen CCG. Task-Level vs. Segment-Level Quantitative Metrics for Surgical Skill Assessment. Journal of Surgical Education 2016;73(3):482
    CrossRef
  4. Juusola JL, Quisel TR, Foschini L, Ladapo JA. The Impact of an Online Crowdsourcing Diagnostic Tool on Health Care Utilization: A Case Study Using a Novel Approach to Retrospective Claims Analysis. Journal of Medical Internet Research 2016;18(6):e127
    CrossRef
  5. Carter RR, Sun J, Jump RLP. A Survey and Analysis of the American Public's Perceptions and Knowledge About Antibiotic Resistance. Open Forum Infectious Diseases 2016;3(3)
    CrossRef
  6. DePalma MT, Rizzotti MC, Branneman M. Assessing Diabetes-Relevant Data Provided by Undergraduate and Crowdsourced Web-Based Survey Participants for Honesty and Accuracy. JMIR Diabetes 2017;2(2):e11
    CrossRef
  7. Brady CJ, Mudie LI, Wang X, Guallar E, Friedman DS. Improving Consensus Scoring of Crowdsourced Data Using the Rasch Model: Development and Refinement of a Diagnostic Instrument. Journal of Medical Internet Research 2017;19(6):e222
    CrossRef
  8. Dai JC, Lendvay TS, Sorensen MD. Crowdsourcing in Surgical Skills Acquisition: A Developing Technology in Surgical Education. Journal of Graduate Medical Education 2017;9(6):697
    CrossRef
  9. Wang X, Mudie LI, Baskaran M, Cheng C, Alward WL, Friedman DS, Brady CJ. Crowdsourcing to Evaluate Fundus Photographs for the Presence of Glaucoma. Journal of Glaucoma 2017;26(6):505
    CrossRef
  10. Mortensen K, Hughes TL. Comparing Amazon’s Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature. Journal of General Internal Medicine 2018;33(4):533
    CrossRef
  11. Ganz M, Kondermann D, Andrulis J, Knudsen GM, Maier-Hein L. Crowdsourcing for error detection in cortical surface delineations. International Journal of Computer Assisted Radiology and Surgery 2017;12(1):161
    CrossRef
  12. Kras A, Celi LA, Miller JB. Accelerating ophthalmic artificial intelligence research: the role of an open access data repository. Current Opinion in Ophthalmology 2020;31(5):337
    CrossRef
  13. Quisel T, Foschini L, Zbikowski SM, Juusola JL. The Association Between Medication Adherence for Chronic Conditions and Digital Health Activity Tracking: Retrospective Analysis. Journal of Medical Internet Research 2019;21(3):e11486
    CrossRef
  14. Créquit P, Mansouri G, Benchoufi M, Vivot A, Ravaud P. Mapping of Crowdsourcing in Health: Systematic Review. Journal of Medical Internet Research 2018;20(5):e187
    CrossRef
  15. Mudie LI, Wang X, Friedman DS, Brady CJ. Crowdsourcing and Automated Retinal Image Analysis for Diabetic Retinopathy. Current Diabetes Reports 2017;17(11)
    CrossRef
  16. Myers E, Stone WL, Bernier R, Lendvay T, Comstock B, Cowan C. The diagnosis conundrum: Comparison of crowdsourced and expert assessments of toddlers with high and low risk of autism spectrum disorder. Autism Research 2018;11(12):1629
    CrossRef
  17. Mamillapalli CK, Prentice JR, Garg AK, Hampsey SL, Bhandari R. Implementation and challenges unique to teleretinal diabetic retinal screening (TDRS) in a private practice setting in the United States. Journal of Clinical & Translational Endocrinology 2020;19:100214
    CrossRef
  18. . Crowdsourcing’s ten years in: A review. Journal of Global Health 2017;7(2)
    CrossRef
  19. Srinivasan S, Shetty S, Natarajan V, Sharma T, Raman R, Bhattacharya S. Development and Validation of a Diabetic Retinopathy Referral Algorithm Based on Single-Field Fundus Photography. PLOS ONE 2016;11(9):e0163108
    CrossRef
  20. Nama N, Sampson M, Barrowman N, Sandarage R, Menon K, Macartney G, Murto K, Vaccani J, Katz S, Zemek R, Nasr A, McNally JD. Crowdsourcing the Citation Screening Process for Systematic Reviews: Validation Study. Journal of Medical Internet Research 2019;21(4):e12953
    CrossRef
  21. Wang X, Mudie L, Brady CJ. Crowdsourcing. Current Opinion in Ophthalmology 2016;27(3):256
    CrossRef
  22. Cole ED, Novais EA, Louzada RN, Waheed NK. Contemporary retinal imaging techniques in diabetic retinopathy: a review. Clinical & Experimental Ophthalmology 2016;44(4):289
    CrossRef
  23. Wang C, Han L, Stein G, Day S, Bien-Gund C, Mathews A, Ong JJ, Zhao P, Wei S, Walker J, Chou R, Lee A, Chen A, Bayus B, Tucker JD. Crowdsourcing in health and medical research: a systematic review. Infectious Diseases of Poverty 2020;9(1)
    CrossRef
  24. Horton MB, Silva PS, Cavallerano JD, Aiello LP. Clinical Components of Telemedicine Programs for Diabetic Retinopathy. Current Diabetes Reports 2016;16(12)
    CrossRef
  25. Murchison AP, Haller JA, Mayro E, Hark L, Gower E, Huisingh C, Rhodes L, Friedman DS, Lee DJ, Lam BL. Reaching the Unreachable: Novel Approaches to Telemedicine Screening of Underserved Populations for Vitreoretinal Disease. Current Eye Research 2017;42(7):963
    CrossRef
  26. Kuang J, Argo L, Stoddard G, Bray BE, Zeng-Treitler Q. Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches. Journal of Medical Internet Research 2015;17(12):e281
    CrossRef
  27. Callaghan W, Goh J, Mohareb M, Lim A, Law E. MechanicalHeart. Proceedings of the ACM on Human-Computer Interaction 2018;2(CSCW):1
    CrossRef
  28. Rangrej SB, Sivaswamy J, Srivastava P, El-Baz A. Scan, dwell, decide: Strategies for detecting abnormalities in diabetic retinopathy. PLOS ONE 2018;13(11):e0207086
    CrossRef
  29. Juni MZ, Eckstein MP. The wisdom of crowds for visual search. Proceedings of the National Academy of Sciences 2017;114(21)
    CrossRef
  30. Meyer AN, Longhurst CA, Singh H. Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed. Journal of Medical Internet Research 2016;18(1):e12
    CrossRef
  31. Ausayakhun S, Snyder BM, Ausayakhun S, Nanegrungsunk O, Apivatthakakul A, Narongchai C, Melo JS, Keenan JD. Clinic-Based Eye Disease Screening Using Non-Expert Fundus Photo Graders at the Point of Screening: Diagnostic Validity and Yield. American Journal of Ophthalmology 2021;227:245
    CrossRef
  32. Karani R, Tapiero S, Jefferson FA, Vernez S, Xie L, Larson KN, Osann K, Okhunov Z, Patel RM, Landman J, Clayman RV, Stephany HA. Crowd-Sourced Assessment of Surgical Skills of Urology Resident Applicants: Four-Year Experience. Journal of Surgical Education 2021;78(6):2030
    CrossRef
  33. Sonabend AM, Zacharia BE, Cloney MB, Sonabend A, Showers C, Ebiana V, Nazarian M, Swanson KR, Baldock A, Brem H, Bruce JN, Butler W, Cahill DP, Carter B, Orringer DA, Roberts DW, Sagher O, Sanai N, Schwartz TH, Silbergeld DL, Sisti MB, Thompson RC, Waziri AE, Ghogawala Z, McKhann G. Defining Glioblastoma Resectability Through the Wisdom of the Crowd: A Proof-of-Principle Study. Neurosurgery 2017;80(4):590
    CrossRef
  34. Laurik-Feuerstein KL, Sapahia R, Cabrera DeBuc D, Somfai GM, Grzybowski A. The assessment of fundus image quality labeling reliability among graders with different backgrounds. PLOS ONE 2022;17(7):e0271156
    CrossRef
  35. Ysidron DW, France CR, Yang Y, Mischkowski D. Research participants recruited using online labor markets may feign medical conditions and overreport symptoms: Caveat emptor. Journal of Psychosomatic Research 2022;159:110948
    CrossRef
  36. Harrington K, Zenk SN, Van Horn L, Giurini L, Mahakala N, Kershaw KN. The Use of Food Images and Crowdsourcing to Capture Real-time Eating Behaviors: Acceptability and Usability Study. JMIR Formative Research 2021;5(12):e27512
    CrossRef
  37. Abousy M, Jenny HE, Xun H, Khavanin N, Creighton F, Byrne P, Cooney D, Redett R, Yang R. Personality, Success, and Beyond: The Layperson's Perception of Patients With Facial Transplantation. Journal of Craniofacial Surgery 2022;33(2):385
    CrossRef
  38. Socia D, Brady CJ, West SK, Cockrell RC, Vinetz JM. Detection of trachoma using machine learning approaches. PLOS Neglected Tropical Diseases 2022;16(12):e0010943
    CrossRef
  39. Brady CJ, Cockrell RC, Aldrich LR, Wolle MA, West SK. A Virtual Reading Center Model Using Crowdsourcing to Grade Photographs for Trachoma: Validation Study. Journal of Medical Internet Research 2023;25:e41233
    CrossRef
  40. Rani P, Nangia V, Murthy K, Khanna R, Das T. Community care for diabetic retinopathy and glaucoma in India: A panel discussion. Indian Journal of Ophthalmology 2018;66(7):916
    CrossRef
  41. Wu P, Wu J, Hsieh Y, Chen LC, Cheng T, Wu P, Hsieh B, Huang W, Huang S, Chen W. Comparing the results of manual and automated quantitative corneal neuroanalysing modules for beginners. Scientific Reports 2021;11(1)
    CrossRef
  42. Cho J, Zhang W, Armstrong GW, Cho D, Culican SM. Crowdsourcing and its applications to ophthalmology. Expert Review of Ophthalmology 2023;18(2):113
    CrossRef
  43. Nguyen P, Hsu P. Robust and High-Accessibility Ranking Method for Crowdsourcing-Based Decision Making. Group Decision and Negotiation 2023;32(5):1211
    CrossRef
  44. Sescleifer AM, Francoisse CA, Osborn TA, Rector JD, Lin AY. Seeing Cleft Lip from a New Angle: Crowdsourcing to Determine whether Scar Severity or Lip Angle Matters More to the General Public. Plastic & Reconstructive Surgery 2023;152(1):126e
    CrossRef
  45. . A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health. Journal of Medical Internet Research 2024;26:e51138
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.3807):

  1. Dai JC, Sorensen MD. Surgeons as Educators. 2018. Chapter 6:93
    CrossRef
  2. Lombi L, Mori L. Health and Illness in the Neoliberal Era in Europe. 2020. :91
    CrossRef