Xin DUAN

Xin DUAN

Postdoc

Sun Yat-sen University



Dr. Xin DUAN was a postdoctoral researcher in School of Biomedical Engineering of Sun Yat-sen University. His research interest includes medical image analysis, cancer molecular subtyping. He is currently researching and designing the development of high-throughput in vivo biological (zebrafish) sensing technologies and platforms based on microfluidics and ultrafast optical imaging technologies, and combining them with artificial intelligence technologies for the precise screening of targeted drugs. Now, he continues his academic career at the Shenzhen Campus of Sun Yat-sen Univeristy.

Interests

  • Medical Images
  • Artificial Intelligence

Education

  • PhD in College of Automation, 2016 - 2020

    Harbin Engineering University

  • Visiting Student in Department of Biomedical Sciences, 2015 - 2018

    City University of Hong Kong

  • MEng in College of Automation, 2012 - 2015

    Harbin Engineering University

  • BEng in College of Automation, 2008 - 2012

    Harbin Engineering University

Publications

CT-based radiogenomic analysis dissects intratumor heterogeneity and predicts prognosis of colorectal cancer: a multi-institutional retrospective study
DNA Repair–Related Gene Signature in Predicting Prognosis of Colorectal Cancer Patients
Dissecting Cellular Heterogeneity Based on Network Denoising of scRNA-seq Using Local Scaling Self-Diffusion
Predicting treatment response from longitudinal images using multi-task deep learning
A metabolism-related radiomics signature for predicting the prognosis of colorectal cancer
Multiomics-based colorectal cancer molecular subtyping using local scaling network fusion
Integrating diffusion components of multi-omics datasets with application to cancer molecular subtyping
Multiomics-Based Colorectal Cancer Molecular Subtyping Using Local Scaling Network Fusion
Dissecting cancer heterogeneity based on dimension reduction of transcriptomic profiles using extreme learning machines
Poor-prognosis nasopharyngeal carcinoma as defined by a molecularly distinct subgroup and prediction by a miRNA expression signature