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Fengjuan Zhang

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Review Open access Aug 2026

Prediction of carotid vulnerable plaques in patients with type 2 diabetes using interpretable machine learning models

An interpretable XGBoost model based on six clinical, laboratory, and CGM-derived indicators showed acceptable discrimination, calibration, and clinical net benefit for estimating ultrasound-defined plaque vulnerability among patients with T2DM and established carotid plaque.

Qi Cheng, Feng-Juan Zhang, Han Wang et al. · 0 citations

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