Please use this identifier to cite or link to this item:
Developing Effective Crowdsourcing Systems for Medical Diagnosis: Challenges and Recommendations
|Title:||Developing Effective Crowdsourcing Systems for Medical Diagnosis: Challenges and Recommendations|
|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.|
|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.