Workshop

Playsourcing: a novel concept for knowledge creation in biomedical research

Shadi Albarqouni, Stefan Matl, Maximilian Baust, Nassir Navab, Stefanie Demirci

Deep Learning and Data Labeling for Medical Applications — LABELS 2016 workshop @ MICCAI, Lecture Notes in Computer Science, 2016

Teaser figure

Abstract

Being considered as a valid solution to the lack of ground truth data problem, crowdsourcing has recently gained a lot of attention within the biomedical domain. However, available concepts in life science domain require expert knowledge and thereby restrict the access to only very specific communities. In this paper, we go beyond state-of-the-art and present a novel concept for seamlessly embedding biomedical science into a common game canvas. Besides introducing the visual saliency concept, we thereby essentially eliminate the requirement for prior knowledge. We have further implemented a game to evaluate our novel concept in three different user studies.

Interactive explainer

Coming soon. An interactive Slidev walkthrough of this paper — with live, explorable figures — will appear here. Authors: set slidev: in this page's front matter to the deployed deck URL.

Research themes

Keywords

CrowdsourcingGamification

Lab authors

Cite (BibTeX)
@inproceedings{albarqouni2016playsourcing,
 author = {Albarqouni, Shadi and Matl, Stefan and Baust, Maximilian and Navab, Nassir and Demirci, Stefanie},
 booktitle = {MICCAI Workshop on Deep Learning and Data Labeling for Medical Applications},
 organization = {Springer, Cham},
 pages = {269--277},
 title = {Playsourcing: a novel concept for knowledge creation in biomedical research},
 year = {2016}
}

Related publications