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mHealth Visual Discovery Dashboard

We present Discovery Dashboard, a visual analytics system for exploring large volumes of time series data from mobile medical field studies. Discovery Dashboard offers interactive exploration tools and a data mining motif discovery algorithm to help researchers formulate hypotheses, discover trends...

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Detalles Bibliográficos
Autores principales: Fang, Dezhi, Hohman, Fred, Polack, Peter, Sarker, Hillol, Kahng, Minsuk, Sharmin, Moushumi, al'Absi, Mustafa, Chau, Duen Horng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5771481/
https://www.ncbi.nlm.nih.gov/pubmed/29354812
http://dx.doi.org/10.1145/3123024.3123170
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author Fang, Dezhi
Hohman, Fred
Polack, Peter
Sarker, Hillol
Kahng, Minsuk
Sharmin, Moushumi
al'Absi, Mustafa
Chau, Duen Horng
author_facet Fang, Dezhi
Hohman, Fred
Polack, Peter
Sarker, Hillol
Kahng, Minsuk
Sharmin, Moushumi
al'Absi, Mustafa
Chau, Duen Horng
author_sort Fang, Dezhi
collection PubMed
description We present Discovery Dashboard, a visual analytics system for exploring large volumes of time series data from mobile medical field studies. Discovery Dashboard offers interactive exploration tools and a data mining motif discovery algorithm to help researchers formulate hypotheses, discover trends and patterns, and ultimately gain a deeper understanding of their data. Discovery Dashboard emphasizes user freedom and flexibility during the data exploration process and enables researchers to do things previously challenging or impossible to do — in the web-browser and in real time. We demonstrate our system visualizing data from a mobile sensor study conducted at the University of Minnesota that included 52 participants who were trying to quit smoking.
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spelling pubmed-57714812018-01-17 mHealth Visual Discovery Dashboard Fang, Dezhi Hohman, Fred Polack, Peter Sarker, Hillol Kahng, Minsuk Sharmin, Moushumi al'Absi, Mustafa Chau, Duen Horng Proc ACM Int Conf Ubiquitous Comput Article We present Discovery Dashboard, a visual analytics system for exploring large volumes of time series data from mobile medical field studies. Discovery Dashboard offers interactive exploration tools and a data mining motif discovery algorithm to help researchers formulate hypotheses, discover trends and patterns, and ultimately gain a deeper understanding of their data. Discovery Dashboard emphasizes user freedom and flexibility during the data exploration process and enables researchers to do things previously challenging or impossible to do — in the web-browser and in real time. We demonstrate our system visualizing data from a mobile sensor study conducted at the University of Minnesota that included 52 participants who were trying to quit smoking. 2017-09 /pmc/articles/PMC5771481/ /pubmed/29354812 http://dx.doi.org/10.1145/3123024.3123170 Text en http://creativecommons.org/licenses/by/2.0/ 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.
spellingShingle Article
Fang, Dezhi
Hohman, Fred
Polack, Peter
Sarker, Hillol
Kahng, Minsuk
Sharmin, Moushumi
al'Absi, Mustafa
Chau, Duen Horng
mHealth Visual Discovery Dashboard
title mHealth Visual Discovery Dashboard
title_full mHealth Visual Discovery Dashboard
title_fullStr mHealth Visual Discovery Dashboard
title_full_unstemmed mHealth Visual Discovery Dashboard
title_short mHealth Visual Discovery Dashboard
title_sort mhealth visual discovery dashboard
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5771481/
https://www.ncbi.nlm.nih.gov/pubmed/29354812
http://dx.doi.org/10.1145/3123024.3123170
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