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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2017
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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. |
format | Online Article Text |
id | pubmed-5771481 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
record_format | MEDLINE/PubMed |
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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