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Collaborative Crowdsourcing for the Diagnosis of Rare Genetic Syndromes: The DYSCERNE Experience
Sofia Douzgou1, Yiannis A Pollalis, Athanassios Vozikis
1Department of Economics, University of Piraeus, Piraeus, Greece.
Abstract:
The big-data revolution is creating a challenge for the provision of services in the health sector to keep pace with the expectations of the general population. Utilization of crowdsourcing can impact positively on the quality, cost and speed of healthcare by involving large sections of professionals and the public and creating novel science within an ethical framework. In 2007, the DYSCERNE project was funded by the European Commission Public Health Executive Agency (EU DG Sanco) aimed at setting up a network of expertise for rare dysmorphic disorders. As part of DYSCERNE, a Dysmorphology Diagnostic System was set up to enable clinicians throughout the EU to submit cases electronically for diagnosis using a secure, web-based interface, hosted at specified access points (submitting nodes), in 26 different European countries. DYSCERNE utilized the process of crowdsourcing international expertise for the clinical diagnosis of very rare genetic syndromes of multiple congenital anomalies. This is the first reported account of collaborative crowd sourcing in dysmorphology, as part of a clinical genetics service.
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