Incorporating knowledge of disease-defining hub genes and regulatory network into a machine learning-based model for predicting treatment response in lupus nephritis after the first renal flare

BACKGROUND: Identifying candidates responsive to treatment is important in lupus nephritis (LN) at the renal flare (RF) because an effective treatment can lower the risk of progression to end-stage kidney disease. However, machine learning (ML)-based models that address this issue are lacking. METHO...

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Detalles Bibliográficos
Autores principales: Lee, Ding-Jie, Tsai, Ping-Huang, Chen, Chien-Chou, Dai, Yang-Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9898995/
https://www.ncbi.nlm.nih.gov/pubmed/36737814
http://dx.doi.org/10.1186/s12967-023-03931-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9898995/
https://www.ncbi.nlm.nih.gov/pubmed/36737814
http://dx.doi.org/10.1186/s12967-023-03931-z

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