Response to the letter 'testing the effectiveness of MyPROSLE in classifying patients with lupus nephritis'.
- Resource Type
- Article
- Authors
- Toro-Domínguez, Daniel; Martorell-Marugán, Jordi; Martinez-Bueno, Manuel; López-Domínguez, Raúl; Carnero-Montoro, Elena; Barturen, Guillermo; Goldman, Daniel; Petri, Michelle; Carmona-Sáez, Pedro; Alarcón-Riquelme, Marta E
- Source
- Briefings in Bioinformatics. Jan2024, Vol. 25 Issue 1, p1-5. 5p.
- Subject
- *LUPUS nephritis
*MACHINE learning
- Language
- ISSN
- 1467-5463
The article is a response to a letter discussing the effectiveness of a web application called MyPROSLE in classifying patients with lupus nephritis. The authors clarify that MyPROSLE is meant to provide additional information for clinical decisions, not replace standard diagnostic procedures. They address concerns raised in the letter and provide detailed explanations and analysis of MyPROSLE's performance. The authors also discuss the impact of incorporating healthy samples in the analysis and highlight the need for considering multiple performance metrics. They emphasize that MyPROSLE should only be used for research purposes and provide data availability and funding information. [Extracted from the article]