Unsupervised Similarity-Based Risk Stratification for Cardiovascular Events Using Long-Term Time-Series Data
In medicine, one often bases decisions upon a comparative analysis of patient data. In this paper, we build upon this observation and describe similarity-based algorithms to risk stratify patients for major adverse cardiac events. We evolve the traditional approach of comparing patient data in two w...
Main Authors: | , |
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Other Authors: | , |
Format: | Article |
Language: | English |
Published: |
Association for Computing Machinery,
2011-10-24T13:36:08Z.
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Subjects: | |
Online Access: | Get fulltext |