Abstract
The widespread adoption of electronic health records in large health systems, combined with recent advances in data mining and machine learning methods, creates opportunities for the rapid acquisition and translation of knowledge for use in clinical practice. One area of great potential is in risk prediction of chronic progressive diseases from longitudinal medical records. In this Chapter, we illustrate this potential using a case study involving prediction of heart failure. Throughout, we discuss challenges and areas in need of further development.
Original language | English (US) |
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Pages (from-to) | 209-227 |
Number of pages | 19 |
Journal | Intelligent Systems Reference Library |
Volume | 56 |
DOIs | |
State | Published - 2014 |
Externally published | Yes |
Keywords
- Electronic health records
- Hearth failure
- Machine learning
- Prediction models
- Text mining
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems and Management
- Library and Information Sciences