One of the main ways to diagnose a patient with pneumonia is through an image exam. This diagnosis requires specific knowledge, which may not be available in many parts of the world. Collective intelligence has the potential to decrease non-expert error rates. The aim of this study is to assess the feasibility and impact of using collective intelligence to detect pneumonia, with the involvement of the general public, after an online training. To carry out the evaluation, a web tool will be developed, using gamification concepts to promote the engagement of the evaluators who will use the tool. Evaluators will be recruited through social media posts and mailing lists. Some information about the evaluators will be requested, in order to draw a more accurate profile of the users of the tool.
Raposo, Marcel Antunes and Graeml, Alexandre, "Análise do Uso da Inteligência Coletiva na Detecção de Casos de Pneumonia" (2020). ISLA 2020 Proceedings. 22.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.