Using data mining techniques to predict hospitalization of hemodialysis patients
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Predictive models in healthcare include blood glucose level prediction, mortality prediction by clustering electronic health data, and a predictive decision making system for dialysis patients.
“A similar example of using predictive models in healthcare are: blood glucose level prediction [23], mortality prediction by clustering electronic health data [40], and a predictive decision making system for dialysis patients [41].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [41]
The C4.5 algorithm is used when dealing with complex and noisy data; it estimates the error rate of initial nodes and prunes the tree to make a more efficient sub-tree.
“Nowadays, upon dealing with complex and noisy data, the C4.5 algorithm is used which is estimating the error rate of initial nodes and pruning the tree to make a more efficient sub-tree [41,51].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [41]
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- Authors
- Yeh, J.-Y., Wu, T.-H., & Tsao, C.-W.
- Affiliations
- National Chiayi University (TW)
- National Taipei University (TW)
- Corresponding author
- Yeh, Jinn-Yi
- Venue
- Decision Support Systems
- Publisher
- Elsevier BV
- Published
- 2011-01
- Volume
- 50
- Issue
- 2
- Pages
- 439-448
- ISSN
- 0167-9236 (ISSN-L)
- OpenAlex
- W2060695172
- Cited by
- 110
- References
- 30
- Citations by year
- 2025: 5 · 2024: 3 · 2023: 4 · 2022: 6 · 2021: 8 · 2020: 8 · 2019: 8 · 2018: 12 · 2017: 12 · 2016: 9 · 2015: 11 · 2014: 8 · 2013: 6 · 2012: 7
- FWCI
- 9.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Decision Support Systems (publishedVersion)
- Funders
- National Science Council
- Topics
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Nephrology › Dialysis and Renal Disease Management
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Keywords
- hemodialysis, hospitalization prediction, temporal abstraction, temporal patterns, biochemical data, decision support system, clinical decision support
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