Feng GAO

Feng GAO

Professor

Biography

Dr. Feng Gao is a Professor of Medical AI at the Sixth Affiliated Hospital of Sun Yat-sen University and the data analysis lead for the ICGC-ARGO Colorectal Cancer project. Leveraging his interdisciplinary expertise in computer science and oncology, Dr. Gao’s lab is dedicated to building the critical technical infrastructure for the “AI-Native Future Hospital.” By pioneering “AI Doctor 3.0” through multi-agent systems, multimodal foundation models, and intelligent surgical computing, his team is driving the paradigm shift from passive medical tools to autonomous, collaborative clinical intelligence. Using colorectal cancer as a flagship testing ground, Dr. Gao focuses on architecture-driven AI paradigms—rather than mere parameter scaling—to create full-stack, scalable solutions that fundamentally restructure healthcare supply and delivery.

Research Interests

  • Artificial Intelligence
  • Colorectal Cancer

Education

  • Joint PhD in Cancer Biology and Bioinformatics
    City University of Hong Kong & Cornell University
    2015 - 2018
  • Visiting Student in Computer Science and Electronic Engineering
    Kumamoto University
    2007 - 2008
  • BEng in Computer Science and Technology
    Shandong University
    2005 - 2009

Related Publications

† First or co-first author, * Corresponding or co-corresponding author, bold names are lab members

(2020). Conference Paper Integrating diffusion components of multi-omics datasets with application to cancer molecular subtyping. Intelligent Systems for Molecular Biology.
(2020). Conference Paper Development of a novel liquid biopsy test to diagnose and locate gastrointestinal cancers. Journal of Clinical Oncology.
(2020). Journal Article Development and validation of an individualized gene expression-based signature to predict overall survival in metastatic colorectal cancer. Annals of Translational Medicine.
(2020). Journal Article Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma. Cancer Cell International.
(2019). Journal Article Multiomics-Based Colorectal Cancer Molecular Subtyping Using Local Scaling Network Fusion. Journal of Computational Biology.
(2019). Conference Paper Identification, development and validation of a circulating miRNA-based diagnostic signature for early detection of gastric cancer. Annals of Oncology.
(2019). Journal Article A signature of hypoxia-related factors reveals functional dysregulation and robustly predicts clinical outcomes in stage I/II colorectal cancer patients. Cancer Cell International.
(2019). Journal Article Long-Read RNA Sequencing Identifies Alternative Splice Variants in Hepatocellular Carcinoma and Tumor-Specific Isoforms. Hepatology.
(2019). Journal Article An immune-related gene pairs signature predicts overall survival in serous ovarian carcinoma. OncoTargets and Therapy.
(2019). Journal Article DeepCC: a novel deep learning-based framework for cancer molecular subtype classification. Oncogenesis.
(2019). Journal Article An immune-related gene signature predicts prognosis of gastric cancer. Medicine.
(2019). Journal Article Gene expression signature in surgical tissues and endoscopic biopsies identifies high-risk T1 colorectal cancers. Gastroenterology.
(2019). Conference Paper Pathway analysis of hypoxia-related factors in early colorectal cancer patients with poor prognosis.. Journal of Clinical Oncology.
(2019). Conference Paper Immune-related gene signature in predicting prognosis of early-stage colorectal cancer patients. Journal of Clinical Oncology.
(2019). Journal Article RNAMethyPro: a biologically conserved signature of N6-methyladenosine regulators for predicting survival at pan-cancer level. npj Precision Oncology.
(2019). Journal Article Genome-wide discovery of a novel gene-expression signature for the identification of lymph node metastasis in esophageal squamous cell carcinoma. Annals of Surgery.
(2019). Journal Article Molecular subtyping of colorectal cancer: Recent progress, new challenges and emerging opportunities. Seminars in Cancer Biology.
(2019). Journal Article A genomewide transcriptomic approach identifies a novel gene expression signature for the detection of lymph node metastasis in patients with early stage gastric cancer. EBioMedicine.