Area of research
Radiology, Nuclear Medicine and Imaging · Genetics
Research interest
Research interests include Radiomics and Machine Learning in Medical Imaging, Glioma Diagnosis and Treatment, MRI in cancer diagnosis, and Advanced X-ray and CT Imaging.
Single-Cell Transcriptome Atlas Reveals the Underlying Mechanism of Kynurenic Acid in the Regulation of Tumor Immune Microenvironment in Glioblastoma.
Notch signaling in the tumor microenvironment: recent advances and targeted therapeutics.
Machine learning model on multi-omics data enables risk stratification and identifies molecular heterogeneity and therapeutic targets in glioblastoma.
Comparison of MRI and CT based deep learning radiomics analyses and their combination for diagnosing intrahepatic cholangiocarcinoma.
Exploring a recurrence model for atypical meningioma based on multiparametric MRI radiomic and clinical characteristics: a multicenter retrospective cohort study.
Improving radiomics-based differentiation of supratentorial malignant brain tumors preoperatively with diffusion-weighted imaging: A three-class machine learning algorithm.
Pre-Operative Overall Survival Prediction of Diffuse Glioma Enhanced by Longitudinal Data.
Molecular mechanisms and therapeutic significance of Tryptophan Metabolism and signaling in cancer.
Sangerbox 2: Enhanced functionalities and update for a comprehensive clinical bioinformatics data analysis platform.
Biologically interpretable multi-task deep learning pipeline predicts molecular alterations, grade, and prognosis in glioma patients.
Radiomic profiling for insular diffuse glioma stratification with distinct biologic pathway activities.
Biologically interpretable multi-task deep learning pipeline predicts molecular alterations, grade, and prognosis in glioma patients
Noninvasive prediction of BRAF V600E mutation status of pleomorphic xanthoastrocytomas with MRI morphologic features and diffusion-weighted imaging.
Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological images.
Multi-task learning for concurrent survival prediction and semi-supervised segmentation of gliomas in brain MRI
Image-based deep learning identifies glioblastoma risk groups with genomic and transcriptomic heterogeneity: a multi-center study.
Radiomic features from dynamic susceptibility contrast perfusion-weighted imaging improve the three-class prediction of molecular subtypes in patients with adult diffuse gliomas.
Dynamic network reorganization underlying neuroplasticity: the deficits-severity-related language network dynamics in patients with left hemispheric gliomas involving language network.
Imaging phenotypes from MRI for the prediction of glioma immune subtypes from RNA sequencing: A multicenter study.
Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas.
Improving Noninvasive Classification of Molecular Subtypes of Adult Gliomas With Diffusion-Weighted MR Imaging: An Externally Validated Machine Learning Algorithm.
Biological underpinnings of radiomic magnetic resonance imaging phenotypes for risk stratification in IDH wild-type glioblastoma.
Diffusion tensor imaging-based machine learning for IDH wild-type glioblastoma stratification to reveal the biological underpinning of radiomic features.
Glioma survival prediction from whole-brain MRI without tumor segmentation using deep attention network: a multicenter study
Image-based deep learning identifies glioblastoma risk groups with genomic and transcriptomic heterogeneity: a multi-center study
Glioma survival prediction from whole-brain MRI without tumor segmentation using deep attention network: a multicenter study.
Longitudinal assessment of network reorganizations and language recovery in postoperative patients with glioma
Predicting 1p/19q co-deletion status from magnetic resonance imaging using deep learning in adult-type diffuse lower-grade gliomas: a discovery and validation study.
Longitudinal assessment of network reorganizations and language recovery in postoperative patients with glioma.
Niclosamide induces growth inhibition and apoptosis through down-regulation of PDGFRβ and STAT3 in human chondrosarcoma cells