Crowdsourcing—Harnessing the Masses to Advance Health and Medicine, a Systematic Review

By Benjamin L. Ranard, Yoonhee P. Ha, Zachary F. Meisel, D. Asch, Shawndra Hill, L. Becker, A. Seymour, R. Merchant. Journal of general internal medicine, 2013

327 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Science Applications

View Paper: https://www.semanticscholar.org/paper/3353cdf22ed5be4f8c4d706521ddd548b4b87dac

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

1. D. Shapiro
2. Jesse J. Chandler
3. Uri Shalit
4. Jutta Joormann
5. Jonas Everaert
6. Gabriele Paolacci
7. Ana V. Nikcevic
8. Marcantonio M. Spada

Citations in the corpus

• Automated versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition (2017, background): “Indeed, there have been several prominent examples of crowdsourcing scientific tools (Vanschoren et al., 2014; Ranard et al., 2014; Paulhamus et al., 2012).”
• Conducting Clinical Research Using Crowdsourced Convenience Samples. (2016, background): “Crowdsourcing has created numerous opportunities to advance science through the efficient allocation of labor to generate, collect, clean, and transform data (for overviews, see Lintott & Reed 2013, Ranard et al. 2014).”