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: 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)

[thumbnail of FoulquierArthritisRheumatology2022.pdf]
Preview
Text
FoulquierArthritisRheumatology2022.pdf - Accepted Version

Download (3MB) | Preview
Creators:
Foulquier Nathan
Le Dantec Christelle
Bettacchioli Eleonore
Jamin Christophe
Alarcón-Riquelme Marta Eugenia
Pers Jacques-Olivier
Kollaborációs szervezet: PRECISESADS Clinical Consortium
Kollaborációs szervezet PRECISESADS Flow Cytometry Consortium
Kovács László (kollab) MTMT
Balog Attila (kollab) MTMT
Deák Magdolna (kollab) MTMT
Bocskai Márta (kollab) MTMT
Dulic Sonja (kollab) MTMT
Kádár Gabriella (kollab) MTMT
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: University of Szeged (2000-)
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: 10 View citing articles in Web of Science®

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year