Title |
Potential identification of pediatric asthma patients within pediatric research database using low rank matrix decomposition
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Published in |
Journal of Clinical Bioinformatics, September 2013
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DOI | 10.1186/2043-9113-3-16 |
Pubmed ID | |
Authors |
Teeradache Viangteeravat |
Abstract |
Asthma is a prevalent disease in pediatric patients and most of the cases begin at very early years of life in children. Early identification of patients at high risk of developing the disease can alert us to provide them the best treatment to manage asthma symptoms. Often evaluating patients with high risk of developing asthma from huge data sets (e.g., electronic medical record) is challenging and very time consuming, and lack of complex analysis of data or proper clinical logic determination might produce invalid results and irrelevant treatments. In this article, we used data from the Pediatric Research Database (PRD) to develop an asthma prediction model from past All Patient Refined Diagnosis Related Groupings (APR-DRGs) coding assignments. The knowledge gleamed in this asthma prediction model, from both routinely use by physicians and experimental findings, will become fused into a knowledge-based database for dissemination to those involved with asthma patients. Success with this model may lead to expansion with other diseases. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 1 | 7% |
Unknown | 13 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 3 | 21% |
Other | 2 | 14% |
Student > Master | 2 | 14% |
Researcher | 2 | 14% |
Student > Ph. D. Student | 1 | 7% |
Other | 2 | 14% |
Unknown | 2 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 4 | 29% |
Engineering | 3 | 21% |
Computer Science | 2 | 14% |
Agricultural and Biological Sciences | 1 | 7% |
Biochemistry, Genetics and Molecular Biology | 1 | 7% |
Other | 0 | 0% |
Unknown | 3 | 21% |