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Crowdsourcing Knowledge Discovery and Innovations in Medicine
Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous an...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications Inc.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4180345/ https://www.ncbi.nlm.nih.gov/pubmed/25239002 http://dx.doi.org/10.2196/jmir.3761 |
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author | Celi, Leo Anthony Ippolito, Andrea Montgomery, Robert A Moses, Christopher Stone, David J |
author_facet | Celi, Leo Anthony Ippolito, Andrea Montgomery, Robert A Moses, Christopher Stone, David J |
author_sort | Celi, Leo Anthony |
collection | PubMed |
description | Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous and seemingly insolvable questions. But these groups tend to work in isolated environments, and do not communicate or interact effectively. Clinicians are typically buried in the weeds and exigencies of daily practice such that they do not recognize or act on ways to improve knowledge discovery. Researchers may not be able to identify the gaps in clinical knowledge. For data scientists, the main challenge is discerning what is relevant in a domain that is both unfamiliar and complex. Each type of domain expert can contribute skills unavailable to the other groups. “Health hackathons” and “data marathons”, in which diverse participants work together, can leverage the current ready availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented, but functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled. |
format | Online Article Text |
id | pubmed-4180345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | JMIR Publications Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-41803452014-10-02 Crowdsourcing Knowledge Discovery and Innovations in Medicine Celi, Leo Anthony Ippolito, Andrea Montgomery, Robert A Moses, Christopher Stone, David J J Med Internet Res Viewpoint Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous and seemingly insolvable questions. But these groups tend to work in isolated environments, and do not communicate or interact effectively. Clinicians are typically buried in the weeds and exigencies of daily practice such that they do not recognize or act on ways to improve knowledge discovery. Researchers may not be able to identify the gaps in clinical knowledge. For data scientists, the main challenge is discerning what is relevant in a domain that is both unfamiliar and complex. Each type of domain expert can contribute skills unavailable to the other groups. “Health hackathons” and “data marathons”, in which diverse participants work together, can leverage the current ready availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented, but functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled. JMIR Publications Inc. 2014-09-19 /pmc/articles/PMC4180345/ /pubmed/25239002 http://dx.doi.org/10.2196/jmir.3761 Text en ©Leo Anthony Celi, Andrea Ippolito, Robert A Montgomery, Christopher Moses, David J Stone. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 19.09.2014. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Viewpoint Celi, Leo Anthony Ippolito, Andrea Montgomery, Robert A Moses, Christopher Stone, David J Crowdsourcing Knowledge Discovery and Innovations in Medicine |
title | Crowdsourcing Knowledge Discovery and Innovations in Medicine |
title_full | Crowdsourcing Knowledge Discovery and Innovations in Medicine |
title_fullStr | Crowdsourcing Knowledge Discovery and Innovations in Medicine |
title_full_unstemmed | Crowdsourcing Knowledge Discovery and Innovations in Medicine |
title_short | Crowdsourcing Knowledge Discovery and Innovations in Medicine |
title_sort | crowdsourcing knowledge discovery and innovations in medicine |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4180345/ https://www.ncbi.nlm.nih.gov/pubmed/25239002 http://dx.doi.org/10.2196/jmir.3761 |
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