Clinical Data Analytics With Time-Related Graphical User Interfaces: Application to Pharmacovigilance

Autor: Thibault Ledieu, Guillaume Bouzillé, Elisabeth Polard, Catherine Plaisant, Frantz Thiessard, Marc Cuggia

Publikováno v: Frontiers in Pharmacology, Vol 9 (2018)

Pharmacovigilance consists in monitoring and preventing the occurrence of adverse drug reactions. This activity can be time-consuming because it requires the collection of both patient and medication information. In this paper, we present two visuali

Externí odkaz: https://doaj.org/article/1e4eb8c38d3f420499986c9101ced716

Do You Believe Your (Social Media) Data? A Personal Story on Location Data Biases, Errors, and Plausibility as Well as Their Visualization

Autor: Tobias Isenberg, Zujany Salazar, Rafael Blanco, Catherine Plaisant

Publikováno v: IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics, 2022, 28 (9), pp.3277-3291. ⟨10.1109/TVCG.2022.3141605⟩
IEEE Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TVCG.2022.3141605⟩

We present a case study on a journey about a personal data collection of carnivorous plant species habitats, and the resulting scientific exploration of location data biases, data errors, location hiding, and data plausibility. While initially driven

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8334d83b6300f75336396b0feb2fb09
https://doi.org/10.1109/tvcg.2022.3141605

Understanding Barriers to Network Exploration With Visualization: A Report from the Trenches

Autor: Mashael AlKadi, Vanessa Serrano, James Scott-Brown, Catherine Plaisant, Jean-Daniel Fekete, Uta Hinrichs, Benjamin Bach

Publikováno v: Alkadi, M, Serrano, V, Scott-Brown, J, Plaisant, C, Fekete, J-D, Hinrichs, U & Bach, B 2023, ' Understanding Barriers to Network Exploration with Visualization: A Report from the Trenches ', IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 1, pp. 907-917 . https://doi.org/10.1109/TVCG.2022.3209487
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics, 2023, 29 (1), pp.907-917. ⟨10.1109/TVCG.2022.3209487⟩

This article reports on an in-depth study that investigates barriers to network exploration with visualizations. Networkvisualization tools are becoming increasingly popular, but little is known about how analysts plan and engage in the visual explor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2bf05780909775b92008b1e4c74c2592
https://pubmed.ncbi.nlm.nih.gov/36155459

EventAction

Autor: Ben Shneiderman, Fan Du, Kenyon Crowley, Neil Spring, Catherine Plaisant

Publikováno v: ACM Transactions on Interactive Intelligent Systems. 9:1-31

People use recommender systems to improve their decisions; for example, item recommender systems help them find films to watch or books to buy. Despite the ubiquity of item recommender systems, they can be improved by giving users greater transparenc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6df58b7bcb7311afb0fcc28f88579edd
https://doi.org/10.1145/3301402

Analyzing Dynamic Hypergraphs with Parallel Aggregated Ordered Hypergraph Visualization

Autor: Paolo Buono, Jean-Daniel Fekete, Nicole Dufournaud, Paola Valdivia, Catherine Plaisant

Publikováno v: IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics, 2021, 27 (1), pp.1-13. ⟨10.1109/TVCG.2019.2933196⟩
IEEE Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers, 2021, 27 (1), pp.1-13. ⟨10.1109/TVCG.2019.2933196⟩

International audience; Parallel Aggregated Ordered Hypergraph (PAOH) is a novel technique to visualize dynamic hypergraphs. Hypergraphs are a generalization of graphs where edges can connect several vertices. Hypergraphs can be used to model network

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::75c60d98985bc08a2f73d9df69dd879f
https://inria.hal.science/hal-02264960/file/Paohvis.pdf