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

(2021). Journal Article Genome-Wide analysis reveals hypoxic microenvironment is associated with immunosuppression in poor survival of stage II/III colorectal cancer patients. Frontiers in Medicine.
(2021). Conference Paper Multi-omics longitudinal analyses in stages I to III CRC patients: Surveillance liquid biopsy test to predict early recurrence and enable risk-stratified postoperative CRC management.. Journal of Clinical Oncology.
(2021). Conference Paper Integrated immune-related gene signature to predict clinical outcome for patients with luminal B breast cancer.. Journal of Clinical Oncology.
(2021). Conference Paper Su029 INTEGRATING PROGNOSIS-RELATED GENES WITH IMMUNE-RELATED GENE SIGNATURE FOR SURVIVAL STRATIFICATION OF EARLY-STAGE COLORECTAL CANCER. Gastroenterology.
(2021). Conference Paper Deep transformers for fast small intestine grounding in capsule endoscope video. IEEE International Symposium on Biomedical Imaging.
(2021). Journal Article Predicting treatment response from longitudinal images using multi-task deep learning. Nature Communications.
(2021). Journal Article A novel cell-free DNA methylation-based model improves the early detection of colorectal cancer. Molecular Oncology.
(2021). Journal Article Identification of prognostic spatial organization features in colorectal cancer microenvironment using deep learning on histopathology images. Medicine in Omics.
(2021). Journal Article Protein-protein interaction analysis reveals a novel cancer stem cell related target TMEM17 in colorectal cancer. Cancer Cell International.
(2020). Book Chapter Genome-wide Discovery of MicroRNA Biomarkers for Cancer Precision Medicine. Detection Methods in Precision Medicine.
(2020). Conference Paper Automatic and interpretable model for periodontitis diagnosis in panoramic radiographs. Medical Image Computing and Computer Assisted Intervention.
(2020). Conference Paper Identification of a stemness-related gene signature for predicting prognosis of patients with adjuvant chemotherapy in colorectal cancer. Annals of Oncology.
(2020). Journal Article Immune-related gene signature in predicting prognosis of early-stage colorectal cancer patients. European Journal of Surgical Oncology.
(2020). Journal Article Multiomics-based colorectal cancer molecular subtyping using local scaling network fusion. Journal of Computational Biology.
(2020). Journal Article Hippo-YAP signaling controls lineage differentiation of mouse embryonic stem cells through modulating the formation of super-enhancers. Nucleic Acids Research.