Playsourcing: A novel concept for knowledge creation in biomedical research
Albarqouni S, Matl S, Baust M, Navab N, Demirci S (2016)
Publication Type: Conference contribution
Publication year: 2016
Journal
Publisher: Springer Verlag
Book Volume: 10008 LNCS
Pages Range: 269-277
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Athens, GRC
ISBN: 9783319469751
DOI: 10.1007/978-3-319-46976-8_28
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.
Involved external institutions
Germany (DE)How to cite
APA:
Albarqouni, S., Matl, S., Baust, M., Navab, N., & Demirci, S. (2016). Playsourcing: A novel concept for knowledge creation in biomedical research. In Zhi Lu, Vasileios Belagiannis, Joao Manuel R.S. Tavares, Jaime S. Cardoso, Andrew Bradley, Joao Paulo Papa, Jacinto C. Nascimento, Marco Loog, Julien Cornebise, Gustavo Carneiro, Diana Mateus, Loic Peter (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 269-277). Athens, GRC: Springer Verlag.
MLA:
Albarqouni, Shadi, et al. "Playsourcing: A novel concept for knowledge creation in biomedical research." Proceedings of the 1st International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016 and 2nd International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2016, Athens, GRC Ed. Zhi Lu, Vasileios Belagiannis, Joao Manuel R.S. Tavares, Jaime S. Cardoso, Andrew Bradley, Joao Paulo Papa, Jacinto C. Nascimento, Marco Loog, Julien Cornebise, Gustavo Carneiro, Diana Mateus, Loic Peter, Springer Verlag, 2016. 269-277.
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