Dr. Feng Gao is a Professor of Colorectal Surgery at the Sixth Affiliated Hospital of Sun Yat-sen University, a position supported by the university’s prestigious 100 Top Talents Program. After initial training in computer engineering and brief roles in engineering and finance, Dr. Gao earned his Ph.D. in cancer research, specializing in the application of artificial intelligence and big data technologies. He is a core member of the International Cancer Genome Consortium - Accelerated Research in Genomic Oncology (ICGC-ARGO) Colorectal Cancer (CRC) project. His research primarily focuses on creating AI-driven solutions for colorectal cancer diagnosis and prognosis. Dr. Gao also has a strong interest in translating these cutting-edge techniques to other medical disciplines, including diabetes, reproductive health, pediatrics, and dentistry.
Interests
- Artificial Intelligence
- Colorectal Cancer
Education
Joint PhD in Cancer Biology and Bioinformatics, 2015 - 2018
City University of Hong Kong & Cornell University
Visiting Student in Computer Science and Electronic Engineering, 2007 - 2008
Kumamoto University
BEng in Computer Science and Technology, 2005 - 2009
Shandong University
Latest
- Interpretable Multimodal Fusion Model for Bridged Histology and Genomics Survival Prediction in Pan-Cancer
- Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis
- Liquid biopsy to identify Barrett's oesophagus, dysplasia and oesophageal adenocarcinoma: the EMERALD multicentre study
- Anatomic association between the gastrocolic trunk of Henle and right colic artery by high-quality CT venography
- Integrated immune-related gene signature predicts clinical outcome for patients with Luminal B breast cancer
- Single-cell encoded gene silencing for high-throughput combinatorial siRNA screening
- Deciphering Tertiary Lymphoid Structure Heterogeneity Reveals Prognostic Signature and Therapeutic Potentials for Colorectal Cancer: A Multicenter Retrospective Cohort Study
- TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology
- Cross-Level Contrastive Learning and Consistency Constraint for Semi-Supervised Medical Image Segmentation
- Structure Embedded Nucleus Classification for Histopathology Images
- Editorial: Clinical risk assessment and intervention of gastrointestinal tumors driven by big-data
- Genome-wide study reveals novel roles for formin-2 in axon regeneration as a microtubule dynamics regulator and therapeutic target for nerve repair
- A Longitudinal MRI-Based Artificial Intelligence System to Predict Pathological Complete Response After Neoadjuvant Therapy in Rectal Cancer: A Multicenter Validation Study
- A prognostic model for ovarian neoplasms established by an integrated analysis of 1580 transcriptomic profiles
- Deep learning-derived spatial organization features on histology images predicts prognosis in colorectal liver metastasis patients after hepatectomy
- Multi-scope Analysis Driven Hierarchical Graph Transformer for Whole Slide Image Based Cancer Survival Prediction
- The landscape of objective response rate of anti-PD-1/L1 monotherapy across 31 types of cancer: a system review and novel biomarker investigating
- Senescence-based colorectal cancer subtyping reveals distinct molecular characteristics and therapeutic strategies
- Deep learning-derived spatial organization features on histopathology images to predict prognosis in patients with colorectal liver metastasis, after hepatectomy.
- Immunological profiling of human colorectal cancer defines four distinct molecular subtypes
- Senescence-Based Colorectal Cancer Subtyping Reveals Distinct Molecular Characteristics and Therapeutic Strategies
- An immune, stroma, and epithelial--mesenchymal transition-related signature for predicting recurrence and chemotherapy benefit in stage II--III colorectal cancer
- MiR-423-5p is a novel endogenous control for the quantification of circulating miRNAs in human esophageal squamous cell carcinoma
- Editorial: Medical knowledge-assisted machine learning technologies in individualized medicine
- Exploring multi-omics latent embedding spaces for characterizing tumor heterogeneity and tumoral fitness effects
- Medical knowledge-assisted machine learning technologies in individualized medicine
- CT-based radiogenomic analysis dissects intratumor heterogeneity and predicts prognosis of colorectal cancer: a multi-institutional retrospective study
- Predicting prognosis and immunotherapy response among colorectal cancer patients based on a tumor immune microenvironment-related lncRNA signature
- Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images
- A transcription factor signature can identify the CMS4 subtype and stratify the prognostic risk of colorectal cancer
- A tumor immune microenvironment-related lncRNA signature for the prognosis and immunotherapeutic sensitivity prediction in colorectal cancer.
- Multi-size deep learning based preoperative computed tomography signature for prognosis prediction of colorectal cancer
- PIANOS: A platform independent and normalization free single-sample classifier for colorectal cancer
- The growth pattern of liver metastases on MRI predicts early recurrence in patients with colorectal cancer: a multicenter study
- Cross-level contrastive learning and consistency constraint for semi-supervised medical image segmentation
- DNA Repair–Related Gene Signature in Predicting Prognosis of Colorectal Cancer Patients
- A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study
- Single-cell RNA-seq recognized the initiator of epithelial ovarian cancer recurrence
- Dissecting Cellular Heterogeneity Based on Network Denoising of scRNA-seq Using Local Scaling Self-Diffusion
- Lesion-aware dynamic kernel for polyp segmentation
- Identification of an autophagy-related gene signature for the prediction of prognosis in early-stage colorectal cancer
- Cancer-associated fibroblasts impact the clinical outcome and treatment response in colorectal cancer via immune system modulation: a comprehensive genome-wide analysis
- OCaMIR—a noninvasive, diagnostic signature for early-stage ovarian cancer: a multi-cohort retrospective and prospective study
- An interpretable computer-aided diagnosis method for periodontitis from panoramic radiographs
- Genome-Wide analysis reveals hypoxic microenvironment is associated with immunosuppression in poor survival of stage II/III colorectal cancer patients
- A model combing an immune-related genes signature and an extracellular matrix-related genes signature in predicting prognosis of left-and right-sided colon cancer
- Deep learning to identify a gene signature associated with molecular subtypes that predicts prognosis in colorectal cancer.
- Genome-wide analysis indicating cancer associated fibroblast (CAF) impacts on colorectal cancer (CRC) prognosis via immunosuppression.
- Identifying an immune-related gene-pair for prognosis prediction of metastatic colorectal cancer.
- Integrated immune-related gene signature to predict clinical outcome for patients with luminal B breast cancer.
- 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.
- Su029 INTEGRATING PROGNOSIS-RELATED GENES WITH IMMUNE-RELATED GENE SIGNATURE FOR SURVIVAL STRATIFICATION OF EARLY-STAGE COLORECTAL CANCER
- Deep transformers for fast small intestine grounding in capsule endoscope video
- Predicting treatment response from longitudinal images using multi-task deep learning
- A novel cell-free DNA methylation-based model improves the early detection of colorectal cancer
- Identification of prognostic spatial organization features in colorectal cancer microenvironment using deep learning on histopathology images
- A metabolism-related radiomics signature for predicting the prognosis of colorectal cancer
- Protein-protein interaction analysis reveals a novel cancer stem cell related target TMEM17 in colorectal cancer
- Genome-wide Discovery of MicroRNA Biomarkers for Cancer Precision Medicine
- Automatic and interpretable model for periodontitis diagnosis in panoramic radiographs
- Identification of a stemness-related gene signature for predicting prognosis of patients with adjuvant chemotherapy in colorectal cancer
- Immune-related gene signature in predicting prognosis of early-stage colorectal cancer patients
- Multiomics-based colorectal cancer molecular subtyping using local scaling network fusion
- Hippo-YAP signaling controls lineage differentiation of mouse embryonic stem cells through modulating the formation of super-enhancers
- Integrating diffusion components of multi-omics datasets with application to cancer molecular subtyping
- Roscovitine enhances All-trans retinoic acid (ATRA)-induced leukemia cell differentiation: Novel effects on signaling molecules for a putative Cdk2 inhibitor
- Development of a novel liquid biopsy test to diagnose and locate gastrointestinal cancers
- Roscovitine enhances all-trans retinoic acid (ATRA)-induced nuclear enrichment of an ensemble of activated signaling molecules and augments ATRA-induced myeloid cell differentiation
- Development and validation of an individualized gene expression-based signature to predict overall survival in metastatic colorectal cancer
- Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma
- Multiomics-Based Colorectal Cancer Molecular Subtyping Using Local Scaling Network Fusion
- Identification, development and validation of a circulating miRNA-based diagnostic signature for early detection of gastric cancer
- A signature of hypoxia-related factors reveals functional dysregulation and robustly predicts clinical outcomes in stage I/II colorectal cancer patients
- Long-Read RNA Sequencing Identifies Alternative Splice Variants in Hepatocellular Carcinoma and Tumor-Specific Isoforms
- An immune-related gene pairs signature predicts overall survival in serous ovarian carcinoma
- DeepCC: a novel deep learning-based framework for cancer molecular subtype classification
- An immune-related gene signature predicts prognosis of gastric cancer
- Gene expression signature in surgical tissues and endoscopic biopsies identifies high-risk T1 colorectal cancers
- Immune-related gene signature in predicting prognosis of early-stage colorectal cancer patients
- Pathway analysis of hypoxia-related factors in early colorectal cancer patients with poor prognosis.
- Genome-wide discovery of a novel gene-expression signature for the identification of lymph node metastasis in esophageal squamous cell carcinoma
- RNAMethyPro: a biologically conserved signature of N6-methyladenosine regulators for predicting survival at pan-cancer level
- Molecular subtyping of colorectal cancer: Recent progress, new challenges and emerging opportunities
- A genomewide transcriptomic approach identifies a novel gene expression signature for the detection of lymph node metastasis in patients with early stage gastric cancer
- Retinoic acid and 6-formylindolo(3,2-b)carbazole (FICZ) combination therapy reveals putative targets for enhancing response in non-APL AML
- High-throughput three-dimensional chemotactic assays reveal steepness-dependent complexity in neuronal sensation to molecular gradients
- Dissecting cancer heterogeneity based on dimension reduction of transcriptomic profiles using extreme learning machines
- Genome-wide discovery and identification of a novel miRNA signature for recurrence prediction in stage II and III colorectal cancer
- A Novel Non-Invasive Circulating Mirna Signature for Detection of Esophageal Adenocarcinoma
- Dysregulation of m6A RNA methylation regulators in colorectal cancer: Clinical implication as prognostic biomarkers and potential therapeutic targets
- A microRNA signature associated with metastasis of T1 colorectal cancers to lymph nodes
- Potential for subsets of wt-NPM1 primary AML blasts to respond to retinoic acid treatment
- HTSanalyzeR2: An Ultra-Fast R/Bioconductor Package for High-Throughput Screens with Interactive Report
- Poor-prognosis nasopharyngeal carcinoma as defined by a molecularly distinct subgroup and prediction by a miRNA expression signature
- A Novel Mirna Signature for the Detection of Lymph Node Metastasis in Submucosal Colorectal Cancer Patients
- A Novel Mirna-Based, Non-Invasive, Diagnostic Panel for Detection of Esophageal Squamous Cell Carcinoma
- Genome-Wide Analysis Revealed a Robust Gene Expression Signature to Identify Lymph Node Metastasis in Submucosal Colorectal Cancer
- Genome-wide discovery and identification of a novel microrna signature for recurrence prediction in colorectal cancer
- Identification, Development and Validation of a Circulating Mirna-Based Diagnostic Signature for Early Detection of Gastric Cancer
- Biomarkers for Precision Medicine