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| The crowdsourcing process in eight steps. (Photo credit: Wikipedia) |
In our discussion on the #DicoDerm initiative we discussed the challenges of the newly emerging online dermatology diagnosis. We also touched upon the growing importance of crowdsourcing in dermatological diagnosis. As the facebook kawasaki diagnosis story demonstrates crowdsourcing is here to stay. Patient privacy is the prime concern in the use of social media platforms such as facebook for clinical diagnosis. Dr Howard Green’s DermGrandRounds initiative introduces a secure platform for crowdsourcing that takes it to an exciting new level of gamification! Dermatologists and other associated clinicians participate in a competition to collectively identify difficult dermatology clinical images in a “gamified” process of crowd intelligence. DermGrandRounds also has a dermatology specific wiki. The highest contributors to the crowd sourced diagnosis and the dermatology wiki are rewarded twice weekly. There are no regional barriers to who can participate. DermGrandRounds has a mobile app as well.
On behalf of Dermatologists Sans Borders and on my behalf, congratulations to Dr Green for this initiative. Our work on standardization and metadata enrichment of clinical images (#SkinHelpDesk and #DicoDerm)may also be helpful in extending DermGrandRounds!
- Machine learning-based BOTOX API - April 11, 2023
- Skinmesh: Machine learning for facial analysis - November 10, 2020
- Free Dermatology EMR for Machine Learning and Artificial Intelligence - January 2, 2020
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