Abstract
The cause of irritable bowel syndrome (IBS), a chronic disorder characterized by abdominal pain and disturbed bowel habits, is largely unknown. It is believed to be related to physical properties in the gut, central mechanisms in the brain, psychological factors, or a combination of these. To understand the relationships within the gut-brain axis with respect to IBS, large numbers of measurements ranging from stool samples to functional magnetic resonance imaging are collected from patients with IBS and healthy controls. As such, IBS is a typical example in medical research where research turns into a big data analysis challenge. In this chapter we demonstrate the power of interactive visual data analysis and exploration to generate an environment for scientific reasoning and hypothesis formulation for data from multiple sources with different character. Three case studies are presented to show the utility of the presented work.
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Acknowledgements
This work was supported through grants ‘Seeing Organ Function’ from the Knut and Alice Wallenberg Foundation (KAW) grant 2013-0076, the Swedish research council grant 2015-05462, the SeRC (Swedish e-Science Research Center) and the ELLIIT environment for strategic research in Sweden. The presented concepts have been realized using the Inviwo open source visualization framework (www.inviwo.org) presented by Jönsson et al. (2018).
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Jönsson, D. et al. (2019). Visual Analysis for Understanding Irritable Bowel Syndrome. In: Rea, P. (eds) Biomedical Visualisation . Advances in Experimental Medicine and Biology, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-19385-0_8
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DOI: https://doi.org/10.1007/978-3-030-19385-0_8
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