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Open access Sep 2026

Interpretable machine learning models for predicting tocilizumab response in rheumatoid arthritis using clinical data

Approximately 30% of patients with rheumatoid arthritis (RA) do not respond to tocilizumab (TCZ). This study aimed to predict TCZ response using machine learning models trained on clinical data. Baseline and follow-up data from patients with RA treated with TCZ were collected. Seven different machine learning models (l...

Meng-Si Ma, Xin-Ya Chen, Xue Wu et al. · 0 citations
Open access Sep 2026

Serum biomarker dynamics for predicting clinical outcomes and hemorrhagic transformation in acute ischemic stroke:A prospective cohort study.

BACKGROUND Acute ischemic stroke (AIS) has high disability and mortality. Hemorrhagic transformation (HT) is a critical complication related to astrocyte damage, axonal injury and inflammation. GFAP, NfL and IL-6 are closely associated with HT, but 7-day continuous dynamic data are lacking. OBJECTIVE To investigate 7...

Hong-Yan Li, Xue-Gang Meng, Zhuo Li et al. · 0 citations

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