Humane Visual AI: Telling the Stories Behind a Medical Condition
October 13, 2020 Β· Declared Dead Β· π IEEE Transactions on Visualization and Computer Graphics
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Authors
Wonyoung So, Edyta P. Bogucka, Sanja Ε ΔepanoviΔ, Sagar Joglekar, Ke Zhou, Daniele Quercia
arXiv ID
2010.06296
Category
cs.HC: Human-Computer Interaction
Citations
15
Venue
IEEE Transactions on Visualization and Computer Graphics
Last Checked
4 months ago
Abstract
A biological understanding is key for managing medical conditions, yet psychological and social aspects matter too. The main problem is that these two aspects are hard to quantify and inherently difficult to communicate. To quantify psychological aspects, this work mined around half a million Reddit posts in the sub-communities specialised in 14 medical conditions, and it did so with a new deep-learning framework. In so doing, it was able to associate mentions of medical conditions with those of emotions. To then quantify social aspects, this work designed a probabilistic approach that mines open prescription data from the National Health Service in England to compute the prevalence of drug prescriptions, and to relate such a prevalence to census data. To finally visually communicate each medical condition's biological, psychological, and social aspects through storytelling, we designed a narrative-style layered Martini Glass visualization. In a user study involving 52 participants, after interacting with our visualization, a considerable number of them changed their mind on previously held opinions: 10% gave more importance to the psychological aspects of medical conditions, and 27% were more favourable to the use of social media data in healthcare, suggesting the importance of persuasive elements in interactive visualizations.
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