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Crowd-Powered Medical Diagnosis : The Potential of Crowdsourcing for Patients with Rare Diseases

  • With the recent rise in medical crowdsourcing platforms, patients with chronic illnesses increasingly broadcast their medical records to obtain an explanation for their complex health conditions. By providing access to a vast pool of diverse medical knowledge, crowdsourcing platforms have the potential to change the way patients receive a medical diagnosis. We developed a conceptual model that details a set of variables. To further the understanding of crowdsourcing as an emerging phenomenon in health care, we provide a contextualization of the various factors that drive participants to exert effort. For this purpose, we used CrowdMed.com as a platform from which we gathered and examined a unique dataset that involves tasks of diagnosing rare medical conditions. By promoting crowdsourcing as a robust and non-discriminatory alternative to seeking help from traditional physicians, we contribute to the acceptance and adoption of crowdsourcing services in health economics.

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Author:Josephine Fischer, Stefan Arnold, Dilara Yesilbas
Parent Title (German):NextGen Scientific Review
Subtitle (German):Annual Perspectives on Next Generation Science
Publisher:Hochschulverlag Mittweida
Place of publication:Mittweida
Document Type:Final Report
Year of Completion:2023
Publishing Institution:Hochschule Mittweida
Release Date:2023/01/27
GND Keyword:Maschinelles Lernen; Graphentheorie
Page Number:9
First Page:10
Last Page:18
Open Access:Frei zugänglich
Licence (German):License LogoUrheberrechtlich geschützt