Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41556

Developing Effective Crowdsourcing Systems for Medical Diagnosis: Challenges and Recommendations

File SizeFormat 
paper0407.pdf1.21 MBAdobe PDFView/Open

Item Summary

Title: Developing Effective Crowdsourcing Systems for Medical Diagnosis: Challenges and Recommendations
Authors: Sen, Kabir
Ghosh, Kaushik
Keywords: Crowdsourcing Systems
Knowledge
Medical Diagnosis
Rare Diseases
Technology
Issue Date: 04 Jan 2017
Abstract: Diverse 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.
Pages/Duration: 8 pages
URI/DOI: http://hdl.handle.net/10125/41556
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.398
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Global Health IT Strategies Minitrack



Items in ScholarSpace are protected by copyright, with all rights reserved, unless otherwise indicated.