Conference proceeding
Hospital Admission Prediction Using Pre-hospital Variables
2009 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, pp 283-286
01 Jan 2009
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
With the rapid outstripping of healthcare resources by the demands on hospital care, it is important to find more effective and efficient ways for managing care. This research is aimed at developing new admission prediction models using various pre-hospital variables to help hospital estimate the patients to be admitted. We developed a framework of hospital admission prediction and proposed two novel approaches to capture semantics of chief complaints to enhance prediction. Our experiments on a hospital dataset demonstrated that our proposed models outperformed several benchmark methods.
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Details
- Title
- Hospital Admission Prediction Using Pre-hospital Variables
- Creators
- Jiexun Li - Drexel UniversityLifan Guo - Drexel UniversityNeal Handly - Drexel UniversityIEEE
- Publication Details
- 2009 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, pp 283-286
- Series
- IEEE International Conference on Bioinformatics and Biomedicine-BIBM
- Publisher
- IEEE
- Number of pages
- 2
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Emergency Medicine
- Web of Science ID
- WOS:000275900200051
- Scopus ID
- 2-s2.0-74549194991
- Other Identifier
- 991019167783504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Biochemical Research Methods
- Biotechnology & Applied Microbiology
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic