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MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data
Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data have been developed without addressing adaptabilit...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371110/ https://www.ncbi.nlm.nih.gov/pubmed/35957406 http://dx.doi.org/10.3390/s22155849 |
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author | Ollenschläger, Malte Küderle, Arne Mehringer, Wolfgang Seifer, Ann-Kristin Winkler, Jürgen Gaßner, Heiko Kluge, Felix Eskofier, Bjoern M. |
author_facet | Ollenschläger, Malte Küderle, Arne Mehringer, Wolfgang Seifer, Ann-Kristin Winkler, Jürgen Gaßner, Heiko Kluge, Felix Eskofier, Bjoern M. |
author_sort | Ollenschläger, Malte |
collection | PubMed |
description | Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data have been developed without addressing adaptability, usability, and user experience. Therefore, we developed a generic open-source Python package focusing on adaptability, usability, and user experience. The developed package, Machine Learning and Data Analytics (MaD) GUI, enables developers to rapidly create a GUI for their specific use case. Furthermore, MaD GUI enables domain experts without programming knowledge to annotate time-series data and apply algorithms to it. We conducted a small-scale study with participants from three international universities to test the adaptability of MaD GUI by developers and to test the user interface by clinicians as representatives of domain experts. MaD GUI saves up to 75% of time in contrast to using a state-of-the-art package. In line with this, subjective ratings regarding usability and user experience show that MaD GUI is preferred over a state-of-the-art package by developers and clinicians. MaD GUI reduces the effort of developers in creating GUIs for time-series analysis and offers similar usability and user experience for clinicians as a state-of-the-art package. |
format | Online Article Text |
id | pubmed-9371110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93711102022-08-12 MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data Ollenschläger, Malte Küderle, Arne Mehringer, Wolfgang Seifer, Ann-Kristin Winkler, Jürgen Gaßner, Heiko Kluge, Felix Eskofier, Bjoern M. Sensors (Basel) Article Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data have been developed without addressing adaptability, usability, and user experience. Therefore, we developed a generic open-source Python package focusing on adaptability, usability, and user experience. The developed package, Machine Learning and Data Analytics (MaD) GUI, enables developers to rapidly create a GUI for their specific use case. Furthermore, MaD GUI enables domain experts without programming knowledge to annotate time-series data and apply algorithms to it. We conducted a small-scale study with participants from three international universities to test the adaptability of MaD GUI by developers and to test the user interface by clinicians as representatives of domain experts. MaD GUI saves up to 75% of time in contrast to using a state-of-the-art package. In line with this, subjective ratings regarding usability and user experience show that MaD GUI is preferred over a state-of-the-art package by developers and clinicians. MaD GUI reduces the effort of developers in creating GUIs for time-series analysis and offers similar usability and user experience for clinicians as a state-of-the-art package. MDPI 2022-08-05 /pmc/articles/PMC9371110/ /pubmed/35957406 http://dx.doi.org/10.3390/s22155849 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ollenschläger, Malte Küderle, Arne Mehringer, Wolfgang Seifer, Ann-Kristin Winkler, Jürgen Gaßner, Heiko Kluge, Felix Eskofier, Bjoern M. MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data |
title | MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data |
title_full | MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data |
title_fullStr | MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data |
title_full_unstemmed | MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data |
title_short | MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data |
title_sort | mad gui: an open-source python package for annotation and analysis of time-series data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371110/ https://www.ncbi.nlm.nih.gov/pubmed/35957406 http://dx.doi.org/10.3390/s22155849 |
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