GUDM: Automatic Generation of Unified Datasets for Learning and Reasoning in Healthcare Article Swipe
Rahman Ali
,
Muhammad Siddiqi
,
Muhammad Zaffwan Idris
,
Taqdir Ali
,
Shujaat Hussain
,
Eui‐Nam Huh
,
Byeong Ho Kang
,
Sungyoung Lee
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.3390/s150715772
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.3390/s150715772
A wide array of biomedical data are generated and made available to healthcare experts. However, due to the diverse nature of data, it is difficult to predict outcomes from it. It is therefore necessary to combine these diverse data sources into a single unified dataset. This paper proposes a global unified data model (GUDM) to provide a global unified data structure for all data sources and generate a unified dataset by a “data modeler” tool. The proposed tool implements user-centric priority based approach which can easily resolve the problems of unified data modeling and overlapping attributes across multiple datasets. The tool is illustrated using sample diabetes mellitus data. The diverse data sources to generate the unified dataset for diabetes mellitus include clinical trial information, a social media interaction dataset and physical activity data collected using different sensors. To realize the significance of the unified dataset, we adopted a well-known rough set theory based rules creation process to create rules from the unified dataset. The evaluation of the tool on six different sets of locally created diverse datasets shows that the tool, on average, reduces 94.1% time efforts of the experts and knowledge engineer while creating unified datasets.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s150715772
- https://www.mdpi.com/1424-8220/15/7/15772/pdf?version=1435907672
- OA Status
- gold
- Cited By
- 15
- References
- 55
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W1656305839
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Raw OpenAlex JSON
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https://openalex.org/W1656305839Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/s150715772Digital Object Identifier
- Title
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GUDM: Automatic Generation of Unified Datasets for Learning and Reasoning in HealthcareWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2015Year of publication
- Publication date
-
2015-07-02Full publication date if available
- Authors
-
Rahman Ali, Muhammad Siddiqi, Muhammad Zaffwan Idris, Taqdir Ali, Shujaat Hussain, Eui‐Nam Huh, Byeong Ho Kang, Sungyoung LeeList of authors in order
- Landing page
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https://doi.org/10.3390/s150715772Publisher landing page
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https://www.mdpi.com/1424-8220/15/7/15772/pdf?version=1435907672Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/1424-8220/15/7/15772/pdf?version=1435907672Direct OA link when available
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Computer science, Unified Model, Process (computing), Data mining, Set (abstract data type), Machine learning, Data science, Artificial intelligence, Physics, Operating system, Programming language, MeteorologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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15Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 1, 2022: 7, 2021: 1, 2019: 1Per-year citation counts (last 5 years)
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55Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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