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April 19, 2026Lara D. Veeken0 citations

Explainable machine learning for predicting infections that require hospitalization in patients with systemic lupus erythematosus

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CHChun-Te HuangMWMin-Shian WangSTShang-Feng Tsai

Key Points

  • The aim is to create an interpretable machine learning model to predict serious infections in patients with systemic lupus erythematosus (SLE).
  • Developed an interpretable machine learning model for predicting infections
  • Utilized SHAP-based explanations for clinical transparency
  • Conducted a retrospective analysis at a single center
  • The model effectively identifies high-risk individuals for serious infections
  • SHAP explanations enhance understanding of model predictions
  • Further validation is necessary due to the study's limitations

Abstract

We developed an interpretable ML model as a supporting tool for predicting serious infections in SLE patients. The integration of SHAP-based explanations enhances clinical transparency and supports early identification of high-risk individuals, although the single-center, retrospective design warrants external validation in future studies.

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Cite This Study

Huang et al. (2026) studied this question.

synapsesocial.com/papers/69e47321010ef96374d8ef38https://doi.org/10.1093/rheumatology/keag199
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