Machine learning identifies a common signature for anti-SSA/Ro60 antibody expression across autoimmune diseases

Foulquier Nathan and Le Dantec Christelle and Bettacchioli Eleonore and Jamin Christophe and Alarcón-Riquelme Marta Eugenia and Pers Jacques-Olivier and Kollaborációs szervezet: PRECISESADS Clinical Consortium and Kollaborációs szervezet PRECISESADS Flow Cytometry Consortium and Kovács László and Balog Attila and Deák Magdolna and Bocskai Márta and Dulic Sonja and Kádár Gabriella (kollab. közrem.): Machine learning identifies a common signature for anti-SSA/Ro60 antibody expression across autoimmune diseases.
ARTHRITIS & RHEUMATOLOGY. Terjedelem: 31 p.-Azonosító: 42243. ISSN 2326-5191 (2022)

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Item Type: Journal Article
Journal or Publication Title: ARTHRITIS & RHEUMATOLOGY
Date: 2022
Page Range: Terjedelem: 31 p.-Azonosító: 42243
ISSN: 2326-5191
Faculty/Unit: Albert Szent-Györgyi Medical School
Institution: Szegedi Tudományegyetem
Language: English
MTMT rekordazonosító: 32869486
DOI azonosító: https://doi.org/10.1002/art.42243
Date Deposited: 2022. Jun. 10. 12:06
Last Modified: 2022. Jun. 10. 12:06
URI: http://publicatio.bibl.u-szeged.hu/id/eprint/24510
Web of Science® Times Cited: 7 View citing articles in Web of Science®

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