Work in Progress

TIEVis: a Visual Analytics Dashboard for Temporal Information Extracted from Clinical Reports

Authors:

Robin De De Croon,

Artuur Leeuwenberg,

Marie-Francine Moens,

Vero Vanden Vanden Abeele,

Katrien VerbertAuthors Info & Claims

IUI '21 Companion: Companion Proceedings of the 26th International Conference on Intelligent User Interfaces

Pages 34 - 36

https://doi.org/10.1145/3397482.3450731

Published: 14 April 2021 Publication History

Abstract

Clinical reports, as unstructured texts, contain important temporal information. However, it remains a challenge for natural language processing (NLP) models to accurately combine temporal cues into a single coherent temporal ordering of described events. In this paper, we present TIEVis, a visual analytics dashboard that visualizes event-timelines extracted from clinical reports. We present the findings of a pilot study in which healthcare professionals explored and used the dashboard to complete a set of tasks. Results highlight the importance of seeing events in their context, and the ability to manually verify and update critical events in a patient history, as a basis to increase user trust.

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Cited By

Chopra SCarroll JPater J(2024)Providing Context to the "Unknown": Patient and Provider Reflections on Connecting Personal Tracking, Patient-Reported Insights, and EHR Data within a Post-COVID ClinicProceedings of the ACM on Human-Computer Interaction10.1145/36869888:CSCW2(1-34)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686988
Pater JChopra SCarroll JZaccour JNova FToscos TGuha SChang F(2024)Charting the COVID Long Haul Experience - A Longitudinal Exploration of Symptoms, Activity, and Clinical AdherenceProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642827(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642827
Jiang LTran NAli Babar M(2022)Mod2Dash: A Framework for Model-Driven Dashboards GenerationProceedings of the ACM on Human-Computer Interaction10.1145/35345266:EICS(1-28)Online publication date: 17-Jun-2022
https://dl.acm.org/doi/10.1145/3534526

Index Terms

TIEVis: a Visual Analytics Dashboard for Temporal Information Extracted from Clinical Reports

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

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Published In

cover image ACM Conferences

IUI '21 Companion: Companion Proceedings of the 26th International Conference on Intelligent User Interfaces

April 2021

101 pages

ISBN:9781450380188

DOI:10.1145/3397482

Co-chairs:
Katrien Verbert
Katholieke Universiteit Leuven
,
Dennis Parra
Pontificia Universidad Católica de Chile
,
General Chair:
Tracy Hammond
Texas A&M University
,
Program Chairs:
Bart Knijnenburg
Clemson University
,
John O'Donovan
UC Santa Barbara
,
Paul Taele
Texas A&M University

Copyright © 2021 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 14 April 2021

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IUI '21

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IUI '21: 26th International Conference on Intelligent User Interfaces

April 14 - 17, 2021

TX, College Station, USA

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

Chopra SCarroll JPater J(2024)Providing Context to the "Unknown": Patient and Provider Reflections on Connecting Personal Tracking, Patient-Reported Insights, and EHR Data within a Post-COVID ClinicProceedings of the ACM on Human-Computer Interaction10.1145/36869888:CSCW2(1-34)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686988
Pater JChopra SCarroll JZaccour JNova FToscos TGuha SChang F(2024)Charting the COVID Long Haul Experience - A Longitudinal Exploration of Symptoms, Activity, and Clinical AdherenceProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642827(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642827
Jiang LTran NAli Babar M(2022)Mod2Dash: A Framework for Model-Driven Dashboards GenerationProceedings of the ACM on Human-Computer Interaction10.1145/35345266:EICS(1-28)Online publication date: 17-Jun-2022
https://dl.acm.org/doi/10.1145/3534526

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