On the estimation of misclassification probabilities of chronic kidney disease using continuous time hidden Markov models
Introduction: The severity of chronic kidney disease (CKD) is reflected in the form of stages of CKD and can be decided on the basis of estimated glomerular filtration rate (eGFR). The computation of eFGR may have computational and measurement errors which may lead to misclassification of stages. Ob...
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| Main Authors: | , , , |
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| Format: | Book |
| Published: |
Society of Diabetic Nephropathy Prevention,
2019-01-01T00:00:00Z.
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| Online Access: | Connect to this object online. |
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