Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The value of latent class analysis in medical diagnosis
281
Zitationen
2
Autoren
1986
Jahr
Abstract
Assessment of the value of diagnostic indicators such as symptoms and laboratory tests results from calculation of the sensitivity and specificity of the indicators. Knowledge of the rate of occurrence of the disease allows for additional calculations of the error rates in using an indicator. These calculations are accurate only when the data on which they are based are reliable. If the diagnosis, which is used as the criterion for computing the sensitivity and specificity, is not accurate, then the resulting calculations will be in error. We show how a statistical method, latent class analysis, allows for the estimation of the characteristics of indicators even when an accurate diagnosis is unavailable. In addition, the method deals with several indicators at once, and provides a way to combine the information from all the indicators to make a diagnosis.
Ähnliche Arbeiten
A survey on deep learning in medical image analysis
2017 · 13.911 Zit.
pROC: an open-source package for R and S+ to analyze and compare ROC curves
2011 · 13.762 Zit.
Dermatologist-level classification of skin cancer with deep neural networks
2017 · 13.458 Zit.
A survey on Image Data Augmentation for Deep Learning
2019 · 12.052 Zit.
QuPath: Open source software for digital pathology image analysis
2017 · 8.387 Zit.