On the estimation of misclassification probabilities of chronic kidney disease using continuous time hidden Markov models

• Auteurs principaux: Gurprit Grover (Auteur), Alka Sabharwal (Auteur), Shrawan Kumar (Auteur), Arpan Kumar Thakur (Auteur)
• Format: Livre
• Publié: Society of Diabetic Nephropathy Prevention, 2019-01-01T00:00:00Z.
• Sujets: article
• Accès en ligne: Connect to this object online.

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...