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Journal Articles Proceedings of the VLDB Endowment (PVLDB) Year : 2019

COVIZ: A System for Visual Formation and Exploration of Patient Cohorts

Abstract

We demonstrate COVIZ, an interactive system to visually form and explore patient cohorts. COVIZ seamlessly integrates visual cohort formation and exploration, making it a single destination for hypothesis generation. COVIZ is easy to use by medical experts and offers many features: (1) It provides the ability to isolate patient demographics (e.g., their age group and location), health markers (e.g., their body mass index), and treatments (e.g., Ventilation for respiratory problems), and hence facilitates cohort formation; (2) It summarizes the evolution of treatments of a cohort into health trajectories, and lets medical experts explore those trajectories; (3) It guides them in examining different facets of a cohort and generating hypotheses for future analysis; (4) Finally, it provides the ability to compare the statistics and health trajectories of multiple cohorts at once. COVIZ relies on QDS, a novel data structure that encodes and indexes various data distributions to enable their efficient retrieval. Additionally, COVIZ visualizes air quality data in the regions where patients live to help with data interpretations. We demonstrate two key scenarios. In the ecological scenario, we show how COVIZ can be used to explore patient data to generate hypotheses on the health evolution of cohorts. In the case cross-over scenario, we show how COVIZ can be used to generate hypotheses on cohort health and pollution data. A video demonstration of COVIZ is accessible via http://bit.ly/video-coviz.
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Dates and versions

hal-02972576 , version 1 (08-11-2020)

Identifiers

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Cicero Pahins, Behrooz Omidvar-Tehrani, Sihem Amer-Yahia, Valérie Siroux, Jean-Louis Pepin, et al.. COVIZ: A System for Visual Formation and Exploration of Patient Cohorts. Proceedings of the VLDB Endowment (PVLDB), 2019, 12 (12), pp.1822-1825. ⟨10.14778/3352063.3352075⟩. ⟨hal-02972576⟩
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