Author

Ji-Qiang He

2 papers indexed here

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Open access Sep 2026

Interpretable ensemble learning model using intratumoral and peritumoral multi-sequence MR-radiomics predicts high-grade cervical cancer with lymphovascular space invasion

By integrating diverse learning algorithms with multi-sequence MR radiomics (intratumoral and peritumoral) and serum biomarkers, the ENMLR demonstrates robust discriminative performance for predicting HGVI double positivity in CC.

Fei Wang, Chun-Yue Yan, Ji-Qiang He et al. · Frontiers in Oncology · 0 citations

Open access Sep 2026

Interpretable machine learning integrating intra-/peritumoral CT radiomics and serum indicators for predicting poorly differentiated esophageal squamous cell carcinoma

The interpretable ENML model exhibits favorable discriminative capability for predicting poorly differentiated ESCC; however, further multicenter external validation is warranted to confirm its generalizability.

Jun Chen, Ji-Qiang He, Xiao-Jiao Zhang et al. · Frontiers in Oncology · 0 citations