Development of Classification Criteria for the Uveitides.

ABSTRACT:

Purpose

To develop classification criteria for 25 of the most common uveitides.

Design

Machine learning using 5,766 cases of 25 uveitides.

Methods

Cases were collected in an informatics-designed preliminary database. Using formal consensus techniques, a final database was constructed of 4,046 cases achieving supermajority agreement on the diagnosis. Cases were analyzed within uveitic class and were split into a training set and a validation set. Machine learning used multinomial logistic regression with lasso regularization on the training set to determine a parsimonious set of criteria for each disease and to minimize misclassification rates. The resulting criteria were evaluated in the validation set. Accuracy of the rules developed to express the machine learning c

SUBMITTER: Standardization of Uveitis Nomenclature (SUN) Working Group 

PROVIDER: S-EPMC8526627 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature