Published on in Vol 17, No 3 (2015): March

Ranking Adverse Drug Reactions With Crowdsourcing

Ranking Adverse Drug Reactions With Crowdsourcing

Ranking Adverse Drug Reactions With Crowdsourcing

Journals

  1. Lalor J, Wu H, Chen L, Mazor K, Yu H. ComprehENotes, an Instrument to Assess Patient Reading Comprehension of Electronic Health Record Notes: Development and Validation. Journal of Medical Internet Research 2018;20(4):e139 View
  2. Wazny K. Applications of crowdsourcing in health: an overview. Journal of Global Health 2018;8(1) View
  3. 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
  4. Talikka M, Bukharov N, Hayes W, Hofmann-Apitius M, Alexopoulos L, Peitsch M, Hoeng J. Novel approaches to develop community-built biological network models for potential drug discovery. Expert Opinion on Drug Discovery 2017:1 View
  5. Lalor J, Woolf B, Yu H. Improving Electronic Health Record Note Comprehension With NoteAid: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Crowdsourced Workers. Journal of Medical Internet Research 2019;21(1):e10793 View
  6. Zide M, Caswell K, Peterson E, Aberle D, Bui A, Arnold C. Consumers’ Patient Portal Preferences and Health Literacy: A Survey Using Crowdsourcing. JMIR Research Protocols 2016;5(2):e104 View
  7. Smith R, Merchant R. Harnessing the crowd to accelerate molecular medicine research. Trends in Molecular Medicine 2015;21(7):403 View
  8. Banda J, Callahan A, Winnenburg R, Strasberg H, Cami A, Reis B, Vilar S, Hripcsak G, Dumontier M, Shah N. Feasibility of Prioritizing Drug–Drug-Event Associations Found in Electronic Health Records. Drug Safety 2016;39(1):45 View
  9. Dainty K, Vaid H, Brooks S. North American Public Opinion Survey on the Acceptability of Crowdsourcing Basic Life Support for Out-of-Hospital Cardiac Arrest With the PulsePoint Mobile Phone App. JMIR mHealth and uHealth 2017;5(5):e63 View
  10. Lardon J, Abdellaoui R, Bellet F, Asfari H, Souvignet J, Texier N, Jaulent M, Beyens M, Burgun A, Bousquet C. Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review. Journal of Medical Internet Research 2015;17(7):e171 View
  11. P Tafti A, Badger J, LaRose E, Shirzadi E, Mahnke A, Mayer J, Ye Z, Page D, Peissig P. Adverse Drug Event Discovery Using Biomedical Literature: A Big Data Neural Network Adventure. JMIR Medical Informatics 2017;5(4):e51 View
  12. Hendrickx J, van Gastel J, Leysen H, Martin B, Maudsley S, Michel M. High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases. Pharmacological Reviews 2020;72(1):191 View
  13. Valeanu A, Damian C, Marineci C, Negres S. The development of a scoring and ranking strategy for a patient-tailored adverse drug reaction prediction in polypharmacy. Scientific Reports 2020;10(1) View
  14. Zhou L, Parmanto B. Development and Validation of a Comprehensive Well-Being Scale for People in the University Environment (Pitt Wellness Scale) Using a Crowdsourcing Approach: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(4):e15075 View
  15. Wang Z, Monteiro C, Jagodnik K, Fernandez N, Gundersen G, Rouillard A, Jenkins S, Feldmann A, Hu K, McDermott M, Duan Q, Clark N, Jones M, Kou Y, Goff T, Woodland H, Amaral F, Szeto G, Fuchs O, Schüssler-Fiorenza Rose S, Sharma S, Schwartz U, Bausela X, Szymkiewicz M, Maroulis V, Salykin A, Barra C, Kruth C, Bongio N, Mathur V, Todoric R, Rubin U, Malatras A, Fulp C, Galindo J, Motiejunaite R, Jüschke C, Dishuck P, Lahl K, Jafari M, Aibar S, Zaravinos A, Steenhuizen L, Allison L, Gamallo P, de Andres Segura F, Dae Devlin T, Pérez-García V, Ma’ayan A. Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd. Nature Communications 2016;7(1) View
  16. Truitt A, Monsell S, Avins A, Nerenz D, Lawrence S, Bauer Z, Comstock B, Edwards T, Patrick D, Jarvik J, Lavallee D. Prioritizing research topics: a comparison of crowdsourcing and patient registry. Quality of Life Research 2018;27(1):41 View
  17. Sims M, Hodges Shaw M, Gilbertson S, Storch J, Halterman M. Legal and ethical issues surrounding the use of crowdsourcing among healthcare providers. Health Informatics Journal 2019;25(4):1618 View
  18. Washington P, Leblanc E, Dunlap K, Penev Y, Kline A, Paskov K, Sun M, Chrisman B, Stockham N, Varma M, Voss C, Haber N, Wall D. Precision Telemedicine through Crowdsourced Machine Learning: Testing Variability of Crowd Workers for Video-Based Autism Feature Recognition. Journal of Personalized Medicine 2020;10(3):86 View
  19. Chang T, Verma B, Shull T, Moniz M, Kohatsu L, Plegue M, Collins-Thompson K. Crowdsourcing and the Accuracy of Online Information Regarding Weight Gain in Pregnancy: A Descriptive Study. Journal of Medical Internet Research 2016;18(4):e81 View
  20. Li Y, Wang H, Kou N, U L, Gong Z. Crowdsourced top-k queries by pairwise preference judgments with confidence and budget control. The VLDB Journal 2021;30(2):189 View
  21. Lavertu A, Hamamsy T, Altman R. Quantifying the Severity of Adverse Drug Reactions Using Social Media: Network Analysis. Journal of Medical Internet Research 2021;23(10):e27714 View
  22. Yin B, Wei X. Efficient Crowdsourced Pareto-Optimal Queries Over Partial Orders With Quality Guarantee. IEEE Transactions on Emerging Topics in Computing 2022;10(1):297 View
  23. Gao Y, Duan W, Rui H. Does Social Media Accelerate Product Recalls? Evidence from the Pharmaceutical Industry. Information Systems Research 2022;33(3):954 View
  24. Liu J, Gui Y, Rao J, Sun J, Wang G, Ren Q, Qu N, Niu B, Chen Z, Sheng X, Wang Y, Zheng M, Li X. In silico off-target profiling for enhanced drug safety assessment. Acta Pharmaceutica Sinica B 2024 View

Books/Policy Documents

  1. . Meyler's Side Effects of Drugs. View