@misc{10481/92676,
year = {2023},
month = {12},
url = {https://hdl.handle.net/10481/92676},
organization = {Grant PID2020-119032RB-I00 supported by MCIN/AEI/10.13039/501100011033: FEDER and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 831434 (3TR)},
organization = {European Union’s Horizon 2020 research and innovation programme},
organization = {EFPIA},
organization = {FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades (grants P20_00335 and B-CTS-40-UGR20)},
organization = {Aid granted of the ‘Consejería de Transformación Económica, Industria, Conocimiento y Universidades’ (CTEICU), in the 2020 call, being co-financed by the European Union through the European Social Fund (ESF) named ‘Andalucía se mueve con Europa”, within the framework of the Andalusian ESF Operational Program 2014–2020},
organization = {Sara Borrell grant # ISCIII CD18/00149},
organization = {Ministerio de Universidades (Spain’s Government)},
organization = {European Union – NextGenerationEU},
publisher = {Oxford University Press},
keywords = {Systemic lupus erythematosus},
keywords = {Machine learning},
keywords = {Transcriptomics},
title = {Response to the letter ‘testing the effectiveness of MyPROSLE in classifying patients with lupus nephritis’},
doi = {10.1093/bib/bbad454},
author = {Toro-Dominguez, Daniel and Martorell Marugán, Jordi and Martínez Bueno, Manuel and López Domínguez, Raúl and Carnero Montoro, Elena and Barturen, Guillermo and Goldman, Daniel and Petri, Michelle and Carmona Sáez, Pedro and Alarcón Riquelme, Marta Eugenia},
}