Literature DB >> 25888696

Crowdsourcing in biomedicine: challenges and opportunities.

Ritu Khare, Benjamin M Good, Robert Leaman, Andrew I Su, Zhiyong Lu.   

Abstract

The use of crowdsourcing to solve important but complex problems in biomedical and clinical sciences is growing and encompasses a wide variety of approaches. The crowd is diverse and includes online marketplace workers, health information seekers, science enthusiasts and domain experts. In this article, we review and highlight recent studies that use crowdsourcing to advance biomedicine. We classify these studies into two broad categories: (i) mining big data generated from a crowd (e.g. search logs) and (ii) active crowdsourcing via specific technical platforms, e.g. labor markets, wikis, scientific games and community challenges. Through describing each study in detail, we demonstrate the applicability of different methods in a variety of domains in biomedical research, including genomics, biocuration and clinical research. Furthermore, we discuss and highlight the strengths and limitations of different crowdsourcing platforms. Finally, we identify important emerging trends, opportunities and remaining challenges for future crowdsourcing research in biomedicine. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

Entities:  

Keywords:  Amazon Mechanical Turk; big data mining; biomedicine; community challenges; crowdsourcing; games

Mesh:

Year:  2015        PMID: 25888696      PMCID: PMC4719068          DOI: 10.1093/bib/bbv021

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  70 in total

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7.  Crowdsourcing for cognitive science--the utility of smartphones.

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Journal:  Database (Oxford)       Date:  2014-09-22       Impact factor: 3.451

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Review 8.  Ethics in biological anthropology.

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9.  The Acoustic Dissection of Cough: Diving Into Machine Listening-based COVID-19 Analysis and Detection.

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