Developing Effective Crowdsourcing Systems for Medical Diagnosis: Challenges and Recommendations

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dc.contributor.authorSen, Kabir
dc.contributor.authorGhosh, Kaushik
dc.date.accessioned2016-12-29T01:16:16Z
dc.date.available2016-12-29T01:16:16Z
dc.date.issued2017-01-04
dc.description.abstractDiverse medical traditions follow different ‘grammar’ making encapsulation of varied body of knowledge challenging. However, the advances in information technology in the 21st century provide an opportunity to aggregate knowledge from varied cultures and medical traditions to tackle difficult health issues for which no cure has been developed. In addition to accumulating knowledge from wide-ranging sources, an ideal crowdsourcing system (CS) can benefit from the use of appropriate algorithms to choose the best solution. This conceptual paper examines existing classification of crowdsourcing and the various challenges involved with the capture and transmission of medical knowledge. It proposes the steps involved in developing an effective CS for dealing with medical problems. The ideal CS should involve the crowd and medical experts from all across the world, who together with the help of algorithms and other technology features in the CS could provide a useful solution for hard to solve health problems.
dc.format.extent8 pages
dc.identifier.doi10.24251/HICSS.2017.398
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41556
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCrowdsourcing Systems
dc.subjectKnowledge
dc.subjectMedical Diagnosis
dc.subjectRare Diseases
dc.subjectTechnology
dc.titleDeveloping Effective Crowdsourcing Systems for Medical Diagnosis: Challenges and Recommendations
dc.typeConference Paper
dc.type.dcmiText

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