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Published on 29.11.12 in Vol 14, No 6 (2012): Nov-Dec

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

Works citing "Crowdsourcing Malaria Parasite Quantification: An Online Game for Analyzing Images of Infected Thick Blood Smears"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2338):

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

  1. Ponti M, Hillman T, Kullenberg C, Kasperowski D. Getting it Right or Being Top Rank: Games in Citizen Science. Citizen Science: Theory and Practice 2018;3(1)
    CrossRef
  2. Wazny K. Applications of crowdsourcing in health: an overview. Journal of Global Health 2018;8(1)
    CrossRef
  3. Fernández D, Harel D, Ipeirotis P, McAllister T. Statistical considerations for crowdsourced perceptual ratings of human speech productions. Journal of Applied Statistics 2018;:1
    CrossRef
  4. Vera J, Santos G. Can Gamification Contribute to Computer Modeling-Driven Biomedical Research?. Frontiers in Physiology 2018;9
    CrossRef
  5. Sescleifer AM, Francoisse CA, Lin AY. Systematic Review: Online Crowdsourcing to Assess Perceptual Speech Outcomes. Journal of Surgical Research 2018;232:351
    CrossRef
  6. Poostchi M, Silamut K, Maude RJ, Jaeger S, Thoma G. Image analysis and machine learning for detecting malaria. Translational Research 2018;194:36
    CrossRef
  7. Bourquard A, Pablo-Trinidad A, Butterworth I, Sánchez-Ferro , Cerrato C, Humala K, Fabra Urdiola M, Del Rio C, Valles B, Tucker-Schwartz JM, Lee ES, Vakoc BJ, Padera TP, Ledesma-Carbayo MJ, Chen Y, Hochberg EP, Gray ML, Castro-González C. Non-invasive detection of severe neutropenia in chemotherapy patients by optical imaging of nailfold microcirculation. Scientific Reports 2018;8(1)
    CrossRef
  8. Mitsakakis K, Hin S, Müller P, Wipf N, Thomsen E, Coleman M, Zengerle R, Vontas J, Mavridis K. Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach. International Journal of Environmental Research and Public Health 2018;15(2):259
    CrossRef
  9. G. Rodrigo E, Aledo JA, Gámez JA. Machine learning from crowds: A systematic review of its applications. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2018;:e1288
    CrossRef
  10. Ortiz-Ruiz A, Postigo M, Gil-Casanova S, Cuadrado D, Bautista JM, Rubio JM, Luengo-Oroz M, Linares M. Plasmodium species differentiation by non-expert on-line volunteers for remote malaria field diagnosis. Malaria Journal 2018;17(1)
    CrossRef
  11. 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
  12. 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
  13. Irshad H, Oh E, Schmolze D, Quintana LM, Collins L, Tamimi RM, Beck AH. Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method. Scientific Reports 2017;7(1)
    CrossRef
  14. 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
  15. Rhoads DD, Mathison BA, Bishop HS, da Silva AJ, Pantanowitz L. Review of Telemicrobiology. Archives of Pathology & Laboratory Medicine 2016;140(4):362
    CrossRef
  16. Polin MR, Siddiqui NY, Comstock BA, Hesham H, Brown C, Lendvay TS, Martino MA. Crowdsourcing: a valid alternative to expert evaluation of robotic surgery skills. American Journal of Obstetrics and Gynecology 2016;215(5):644.e1
    CrossRef
  17. Michelucci P, Dickinson JL. The power of crowds. Science 2016;351(6268):32
    CrossRef
  18. Wang X, Mudie L, Brady CJ. Crowdsourcing. Current Opinion in Ophthalmology 2016;27(3):256
    CrossRef
  19. Veeman M, Reeves W. Quantitative and in toto imaging in ascidians: Working toward an image-centric systems biology of chordate morphogenesis. genesis 2015;53(1):143
    CrossRef
  20. DAS D, MUKHERJEE R, CHAKRABORTY C. Computational microscopic imaging for malaria parasite detection: a systematic review. Journal of Microscopy 2015;260(1):1
    CrossRef
  21. Chu K, Smith ZJ, Wachsmann-Hogiu S. Development of inexpensive blood imaging systems: where are we now?. Expert Review of Medical Devices 2015;12(5):613
    CrossRef
  22. Cui L, Carter R, Zhang G. Evaluation of a Novel Conjunctive Exploratory Navigation Interface for Consumer Health Information: A Crowdsourced Comparative Study. Journal of Medical Internet Research 2014;16(2):e45
    CrossRef
  23. Kahn MJ, Maurer R, Wartman SA, Sachs BP. A Case for Change. Academic Medicine 2014;89(9):1216
    CrossRef
  24. Ranard BL, Ha YP, Meisel ZF, Asch DA, Hill SS, Becker LB, Seymour AK, Merchant RM. Crowdsourcing—Harnessing the Masses to Advance Health and Medicine, a Systematic Review. Journal of General Internal Medicine 2014;29(1):187
    CrossRef
  25. Jorda J, Sawaya MR, Yeates TO. CrowdPhase: crowdsourcing the phase problem. Acta Crystallographica Section D Biological Crystallography 2014;70(6):1538
    CrossRef
  26. Brady CJ, Villanti AC, Pearson JL, Kirchner TR, Gupta OP, Shah CP. Rapid Grading of Fundus Photographs for Diabetic Retinopathy Using Crowdsourcing. Journal of Medical Internet Research 2014;16(10):e233
    CrossRef
  27. Della Mea V, Maddalena E, Mizzaro S, Machin P, Beltrami CA. Preliminary results from a crowdsourcing experiment in immunohistochemistry. Diagnostic Pathology 2014;9(Suppl 1):S6
    CrossRef
  28. Wilman HR, Ebejer J, Shi J, Deane CM, Knapp B. Crowdsourcing Yields a New Standard for Kinks in Protein Helices. Journal of Chemical Information and Modeling 2014;54(9):2585
    CrossRef
  29. Good BM, Loguercio S, Griffith OL, Nanis M, Wu C, Su AI. The Cure: Design and Evaluation of a Crowdsourcing Game for Gene Selection for Breast Cancer Survival Prediction. JMIR Serious Games 2014;2(2):e7
    CrossRef
  30. Weiner M. The Potential of Crowdsourcing to Improve Patient-Centered Care. The Patient - Patient-Centered Outcomes Research 2014;7(2):123
    CrossRef
  31. Ilakkuvan V, Tacelosky M, Ivey KC, Pearson JL, Cantrell J, Vallone DM, Abrams DB, Kirchner TR. Cameras for Public Health Surveillance: A Methods Protocol for Crowdsourced Annotation of Point-of-Sale Photographs. JMIR Research Protocols 2014;3(2):e22
    CrossRef
  32. Good BM, Su AI. Crowdsourcing for bioinformatics. Bioinformatics 2013;29(16):1925
    CrossRef
  33. Saunders DR, Bex PJ, Woods RL. Crowdsourcing a Normative Natural Language Dataset: A Comparison of Amazon Mechanical Turk and In-Lab Data Collection. Journal of Medical Internet Research 2013;15(5):e100
    CrossRef
  34. Dasgupta N, Freifeld C, Brownstein JS, Menone CM, Surratt HL, Poppish L, Green JL, Lavonas EJ, Dart RC. Crowdsourcing Black Market Prices For Prescription Opioids. Journal of Medical Internet Research 2013;15(8):e178
    CrossRef
  35. Yu B, Willis M, Sun P, Wang J. Crowdsourcing Participatory Evaluation of Medical Pictograms Using Amazon Mechanical Turk. Journal of Medical Internet Research 2013;15(6):e108
    CrossRef
  36. Hill S, Merchant R, Ungar L. Lessons Learned About Public Health from Online Crowd Surveillance. Big Data 2013;1(3):160
    CrossRef
  37. Zhai H, Lingren T, Deleger L, Li Q, Kaiser M, Stoutenborough L, Solti I. Web 2.0-Based Crowdsourcing for High-Quality Gold Standard Development in Clinical Natural Language Processing. Journal of Medical Internet Research 2013;15(4):e73
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.2338)

:
  1. Huang M, Hamarneh G. Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis. 2017. Chapter 13:116
    CrossRef
  2. O’Neil AQ, Murchison JT, van Beek EJR, Goatman KA. Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis. 2017. Chapter 11:96
    CrossRef
  3. Santos CP, van de Haterd J, Hutchinson K, Khan V, Markopoulos P. End-User Development. 2017. Chapter 3:34
    CrossRef
  4. Albarqouni S, Matl S, Baust M, Navab N, Demirci S. Deep Learning and Data Labeling for Medical Applications. 2016. Chapter 28:269
    CrossRef