POS1021 UNSUPERVISED MACHINE-LEARNING ALGORITHM FOR THE IDENTIFICATION OF CLINICAL PHENOTYPES ACROSS PATIENTS INITIATING BELIMUMAB IN THE LUPUS ITALIAN REGISTRY (LIRE) OF THE ITALIAN SOCIETY FOR RHEUMATOLOGY

Background:Stratification of patients affected with systemic autoimmune diseases according to clinical and endotypic features may provide valuable insights to disease mechanisms and expected response to target treatments. Belimumab is increasingly used as add-on therapy in refractory systemic lupus...

Full description

Saved in:

Bibliographic Details
Published in:	Annals of the rheumatic diseases Vol. 83; no. Suppl 1; pp. 987 - 988
Main Authors:	Gatto, M., Venerito, V., Rozza, D., Landolfi, G., Scirè, C. A., Sebastiani, G. D., Conti, F., Doria, A.
Format:	Journal Article
Language:	English
Published:	Kidlington BMJ Publishing Group Ltd and European League Against Rheumatism 01.06.2024 Elsevier B.V Elsevier Limited
Subjects:	Artificial Intelligence Autoimmune diseases Disease Factor analysis Hydroxychloroquine Learning algorithms Lupus Machine learning Monoclonal antibodies Patient-led research Patients Phenotypes Real-world evidence Rheumatology Scientific Abstracts Serology Systemic lupus erythematosus Patient-led research Artificial Intelligence Real-world evidence
ISSN:	0003-4967, 1468-2060
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!