Purpose To determine classification criteria for multifocal choroiditis with panuveitis (MFCPU). Design Machine learning of cases with MFCPU and 8 other posterior uveitides. Methods Cases of posterior uveitides were collected…
Purpose To determine classification criteria for tubercular uveitis. Design Machine learning of cases with tubercular uveitis and 14 other uveitides. Methods Cases of noninfectious posterior uveitis or panuveitis, and of…
ABSTRACT Purpose To determine classification criteria for toxoplasmic retinitis. Design Machine learning of cases with toxoplasmic retinitis and 4 other infectious posterior uveitides / panuveitides. Methods Cases of infectious posterior…
Purpose To determine classification criteria for serpiginous choroiditis. Design Machine learning of cases with serpiginous choroiditis and 8 other posterior uveitides. Methods Cases of posterior uveitides were collected in an…
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….
Purpose To determine classification criteria for cytomegalovirus (CMV) anterior uveitis. Design Machine learning of cases with CMV anterior uveitis and 8 other anterior uveitides. Methods Cases of anterior uveitides were…
Purpose To determine classification criteria for Behçet disease uveitis. Design Machine learning of cases with Behçet disease and 5 other panuveitides. Methods Cases of panuveitides were collected in an informatics-designed…
Purpose The purpose of this study was to determine classification criteria for multiple sclerosis-associated intermediate uveitis. Design Machine learning of cases with multiple sclerosis-associated intermediate uveitis and 4 other intermediate…
Purpose To determine classification criteria for birdshot chorioretinitis. Design Machine learning of cases with birdshot chorioretinitis and 8 other posterior uveitides. Methods Cases of posterior uveitides were collected in an…
Acknowledgment The author recognizes and acknowledges the influence of Drs. Bradley Coffey and Alan W. Reichow for much of the information contained in this chapter. There is significant interest in…
