Data-driven cluster analysis for identifying groups within users of anti-osteoporosis medication, using real-world primary care data.
Data-driven methods can be used for pattern recognition within a clinical population, enriching the existing analytical tools for clinical data analysis. We clustered anti-osteoporosis drug users with similar risk factors, to better determine the influence of therapy on their fracture risk
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Format: | Conference item |
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International Society for Clinical Biostatistics
2017
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