Visual Analytics for Biomedical Applications
by Prof.Dr. Anna Vilanova (Department of Mathematics and Computer Science, at the Eindhoven University of Technology (TU/e))
Visual analytics is a branch of visualization that focuses on analytical reasoning facilitated by interaction and visual representations. Visual analytics is an extension to AI methods. It is also a complement to the already existing visualization techniques by the introduction of the concepts of reasoning and AI. Interaction and enhancement of human reasoning and decision making are central. AI has successfully developed models that outperform humans in several tasks. However, this success is limited when it comes to increasing knowledge, and providing new understanding based on new data. The complexity of the human reasoning and consciousness is often needed to generated new insight. The research in my group has focused on visual analytics for data exploration, hypothesis generation and understanding for biomedical applications, such as, virtual colonoscopy, diffusion weighted imaging for brain white-matter and muscle, and 4D blood flow analysis. For this purpose, we developed interactive visualization strategies, including uncertainties and facilitating the analysis of cohort data. Most recently we worked on the concept of progressive visual analytics and the use of dimensionality reduction as an effective VA component for large high-dimensional data visualization. Visual analytics techniques are also a promising approach to open the black-box AI models.
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