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3 Result(s)

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  1. Article

    Open Access

    Biologically interpretable multi-task deep learning pipeline predicts molecular alterations, grade, and prognosis in glioma patients

    Deep learning models have been developed for various predictions in glioma; yet, they were constrained by manual segmentation, task-specific design, or a lack of biological interpretation. Herein, we aimed to ...

    Xuewei Wu, Shuaitong Zhang, Zhenyu Zhang, Zicong He, Zexin Xu… in npj Precision Oncology (2024)

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  2. No Access

    Article

    An interpretable machine learning model based on contrast-enhanced CT parameters for predicting treatment response to conventional transarterial chemoembolization in patients with hepatocellular carcinoma

    To explore the potential of pre-therapy computed tomography (CT) parameters in predicting the treatment response to initial conventional TACE (cTACE) in intermediate-stage hepatocellular carcinoma (HCC) and de...

    Lu Zhang, Zhe Jin, Chen Li, Zicong He, Bin Zhang, Qiuying Chen… in La radiologia medica (2024)

  3. No Access

    Article

    Carbonic anhydrase IX stratifies patient prognosis and identifies nodal status in animal models of nasopharyngeal carcinoma using a targeted imaging strategy

    Accurate identification of nodal status enables adequate neck irradiation for nasopharyngeal carcinoma (NPC). However, most conventional techniques are unable to pick up occult metastases, leading to underesti...

    Wenhui Huang, Kun Wang, Weiyuan Huang… in European Journal of Nuclear Medicine and M… (2022)