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

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552) Crowdsourcing and Mechanical Turks (90)

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

Rapid Grading of Fundus Photographs for Diabetic Retinopathy Using Crowdsourcing

Rapid Grading of Fundus Photographs for Diabetic Retinopathy Using Crowdsourcing

Rapid Grading of Fundus Photographs for Diabetic Retinopathy Using Crowdsourcing

Authors of this article:

Christopher J Brady1, 2 Author Orcid Image ;   Andrea C Villanti3 Author Orcid Image ;   Jennifer L Pearson3 Author Orcid Image ;   Thomas R Kirchner3 Author Orcid Image ;   Omesh P Gupta1 Author Orcid Image ;   Chirag P Shah4 Author Orcid Image
Article Authors Cited by (47) Tweetations (8) Metrics

Journals

  1. Bouenizabila É, 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 View
  2. Wazny K. Applications of crowdsourcing in health: an overview. Journal of Global Health 2018;8(1) View
  3. Vedula S, Malpani A, Ahmidi N, Khudanpur S, Hager G, Chen C. Task-Level vs. Segment-Level Quantitative Metrics for Surgical Skill Assessment. Journal of Surgical Education 2016;73(3):482 View
  4. Juusola J, Quisel T, Foschini L, Ladapo J. 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 View
  5. Carter R, Sun J, Jump R. A Survey and Analysis of the American Public's Perceptions and Knowledge About Antibiotic Resistance. Open Forum Infectious Diseases 2016;3(3) View
  6. DePalma M, Rizzotti M, 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 View
  7. Brady C, Mudie L, Wang X, Guallar E, Friedman D. 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 View
  8. Dai J, Lendvay T, Sorensen M. Crowdsourcing in Surgical Skills Acquisition: A Developing Technology in Surgical Education. Journal of Graduate Medical Education 2017;9(6):697 View
  9. Wang X, Mudie L, Baskaran M, Cheng C, Alward W, Friedman D, Brady C. Crowdsourcing to Evaluate Fundus Photographs for the Presence of Glaucoma. Journal of Glaucoma 2017;26(6):505 View
  10. Mortensen K, Hughes T. 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 View
  11. Ganz M, Kondermann D, Andrulis J, Knudsen G, Maier-Hein L. Crowdsourcing for error detection in cortical surface delineations. International Journal of Computer Assisted Radiology and Surgery 2017;12(1):161 View
  12. Kras A, Celi L, Miller J. Accelerating ophthalmic artificial intelligence research: the role of an open access data repository. Current Opinion in Ophthalmology 2020;31(5):337 View
  13. Quisel T, Foschini L, Zbikowski S, Juusola J. The Association Between Medication Adherence for Chronic Conditions and Digital Health Activity Tracking: Retrospective Analysis. Journal of Medical Internet Research 2019;21(3):e11486 View
  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 View
  15. Mudie L, Wang X, Friedman D, Brady C. Crowdsourcing and Automated Retinal Image Analysis for Diabetic Retinopathy. Current Diabetes Reports 2017;17(11) View
  16. Myers E, Stone W, 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 View
  17. Mamillapalli C, Prentice J, Garg A, Hampsey S, 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 View
  18. Wazny K. Crowdsourcing’s ten years in: A review. Journal of Global Health 2017;7(2) View
  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 View
  20. Nama N, Sampson M, Barrowman N, Sandarage R, Menon K, Macartney G, Murto K, Vaccani J, Katz S, Zemek R, Nasr A, McNally J. Crowdsourcing the Citation Screening Process for Systematic Reviews: Validation Study. Journal of Medical Internet Research 2019;21(4):e12953 View
  21. Wang X, Mudie L, Brady C. Crowdsourcing. Current Opinion in Ophthalmology 2016;27(3):256 View
  22. Cole E, Novais E, Louzada R, Waheed N. Contemporary retinal imaging techniques in diabetic retinopathy: a review. Clinical & Experimental Ophthalmology 2016;44(4):289 View
  23. Wang C, Han L, Stein G, Day S, Bien-Gund C, Mathews A, Ong J, Zhao P, Wei S, Walker J, Chou R, Lee A, Chen A, Bayus B, Tucker J. Crowdsourcing in health and medical research: a systematic review. Infectious Diseases of Poverty 2020;9(1) View
  24. Horton M, Silva P, Cavallerano J, Aiello L. Clinical Components of Telemedicine Programs for Diabetic Retinopathy. Current Diabetes Reports 2016;16(12) View
  25. Murchison A, Haller J, Mayro E, Hark L, Gower E, Huisingh C, Rhodes L, Friedman D, Lee D, Lam B. Reaching the Unreachable: Novel Approaches to Telemedicine Screening of Underserved Populations for Vitreoretinal Disease. Current Eye Research 2017;42(7):963 View
  26. Kuang J, Argo L, Stoddard G, Bray B, Zeng-Treitler Q. Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches. Journal of Medical Internet Research 2015;17(12):e281 View
  27. Callaghan W, Goh J, Mohareb M, Lim A, Law E. MechanicalHeart. Proceedings of the ACM on Human-Computer Interaction 2018;2(CSCW):1 View
  28. Rangrej S, Sivaswamy J, Srivastava P, El-Baz A. Scan, dwell, decide: Strategies for detecting abnormalities in diabetic retinopathy. PLOS ONE 2018;13(11):e0207086 View
  29. Juni M, Eckstein M. The wisdom of crowds for visual search. Proceedings of the National Academy of Sciences 2017;114(21) View
  30. Meyer A, Longhurst C, Singh H. Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed. Journal of Medical Internet Research 2016;18(1):e12 View
  31. Ausayakhun S, Snyder B, Ausayakhun S, Nanegrungsunk O, Apivatthakakul A, Narongchai C, Melo J, Keenan J. 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 View
  32. Karani R, Tapiero S, Jefferson F, Vernez S, Xie L, Larson K, Osann K, Okhunov Z, Patel R, Landman J, Clayman R, Stephany H. Crowd-Sourced Assessment of Surgical Skills of Urology Resident Applicants: Four-Year Experience. Journal of Surgical Education 2021;78(6):2030 View
  33. Sonabend A, Zacharia B, Cloney M, Sonabend A, Showers C, Ebiana V, Nazarian M, Swanson K, Baldock A, Brem H, Bruce J, Butler W, Cahill D, Carter B, Orringer D, Roberts D, Sagher O, Sanai N, Schwartz T, Silbergeld D, Sisti M, Thompson R, Waziri A, Ghogawala Z, McKhann G. Defining Glioblastoma Resectability Through the Wisdom of the Crowd: A Proof-of-Principle Study. Neurosurgery 2017;80(4):590 View
  34. Laurik-Feuerstein K, Sapahia R, Cabrera DeBuc D, Somfai G, Grzybowski A. The assessment of fundus image quality labeling reliability among graders with different backgrounds. PLOS ONE 2022;17(7):e0271156 View
  35. Ysidron D, France C, 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 View
  36. Harrington K, Zenk S, Van Horn L, Giurini L, Mahakala N, Kershaw K. The Use of Food Images and Crowdsourcing to Capture Real-time Eating Behaviors: Acceptability and Usability Study. JMIR Formative Research 2021;5(12):e27512 View
  37. Abousy M, Jenny H, 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 View
  38. Socia D, Brady C, West S, Cockrell R, Vinetz J. Detection of trachoma using machine learning approaches. PLOS Neglected Tropical Diseases 2022;16(12):e0010943 View
  39. Brady C, Cockrell R, Aldrich L, Wolle M, West S. A Virtual Reading Center Model Using Crowdsourcing to Grade Photographs for Trachoma: Validation Study. Journal of Medical Internet Research 2023;25:e41233 View
  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 View
  41. Wu P, Wu J, Hsieh Y, Chen L, 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) View
  42. Cho J, Zhang W, Armstrong G, Cho D, Culican S. Crowdsourcing and its applications to ophthalmology. Expert Review of Ophthalmology 2023;18(2):113 View
  43. Nguyen P, Hsu P. Robust and High-Accessibility Ranking Method for Crowdsourcing-Based Decision Making. Group Decision and Negotiation 2023;32(5):1211 View
  44. Sescleifer A, Francoisse C, Osborn T, Rector J, Lin A. 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 View
  45. Washington P. A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health. Journal of Medical Internet Research 2024;26:e51138 View

Books/Policy Documents

  1. Dai J, Sorensen M. Surgeons as Educators. View
  2. Lombi L, Mori L. Health and Illness in the Neoliberal Era in Europe. View