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

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

Abstract 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 lackin...

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Bibliographic Details
Main Authors: Ding-Jie Lee, Ping-Huang Tsai, Chien-Chou Chen, Yang-Hong Dai
Format: Article
Language:English
Published: BMC 2023-02-01
Series:Journal of Translational Medicine
Subjects:
Lupus nephritis
Renal flare
Transcriptomics
Machine learning
Prediction model
Online Access:https://doi.org/10.1186/s12967-023-03931-z

Internet

https://doi.org/10.1186/s12967-023-03931-z

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