Feng GAO

Professor

Biography

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.

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

Yuying Wang^†, Jianchao Zheng, Zhilong Li, Ruijingfang Jiang, Jiaxi Peng, Jianlong Sun, Guanghui Yang, Xin-Rong Yang, Ao Huang, Yupeng Wang, Yuan Jie, Xuanhui Liu, Feng GAO, Xiaojian Wu, Dansong Wang, Wenchuan Wu, Wenhui Lou, Jian Zhou, Jia Fan^* (0001). Development of a novel liquid biopsy test to diagnose and locate gastrointestinal cancers.

Xinkai Zhao^†, Chaowei Fang, Feng GAO, FAN De-Jun, Xutao Lin, Guanbin Li^* (0001). Deep transformers for fast small intestine grounding in capsule endoscope video.

Xin Wang^†, Yu-Hong Li, Baocai Xing, Lin Qi, Jie-Ying Liang, Zhong-Wu Li, Shao-Yan Xi, Yu-Ni Lai, Feng GAO, De-Shen Wang, Ming-Tao Hu, Yi Cao, Xian-Rui Zhang, Li-Jian Xu, Ronald CK Chan^* (0001). Deep learning-derived spatial organization features on histopathology images to predict prognosis in patients with colorectal liver metastasis, after hepatectomy..

Du CAI^†, Wei Wang, Min-Er ZHONG, De-Jun FAN, Xuanhui Liu, Cheng-Hang LI, Ze-Ping HUANG, Qi-Qi ZHU, Min-Yi LV, Chu-Ling HU, Xin DUAN, Xiaojian Wu, Feng GAO^* (0001). Deep learning to identify a gene signature associated with molecular subtypes that predicts prognosis in colorectal cancer..

Xinkai Zhao^†, Chaowei Fang, De-Jun FAN, Xutao Lin, Feng GAO, Guanbin Li^* (0001). Cross-Level Contrastive Learning and Consistency Constraint for Semi-Supervised Medical Image Segmentation.

Xinkai Zhao^†, Chaowei Fang, De-Jun FAN, Xutao Lin, Feng GAO, Guanbin Li^* (0001). Cross-level contrastive learning and consistency constraint for semi-supervised medical image segmentation.

Haoyang Li^†, Juexiao Zhou, Yi Zhou, Jie-Yu CHEN, Feng GAO, Ying Xu, Xin Gao^* (0001). Automatic and interpretable model for periodontitis diagnosis in panoramic radiographs.

Chu-Ling HU^†, Du CAI, Min-Er ZHONG, De-Jun FAN, Cheng-Hang LI, Min-Yi LV, Ze-Ping HUANG, Wei Wang, Xiaojian Wu, Feng GAO^* (0001). A tumor immune microenvironment-related lncRNA signature for the prognosis and immunotherapeutic sensitivity prediction in colorectal cancer..

Jinsei Miyoshi^†, Feng GAO, Shusuke Toden, Martha J. Shrubsole, Marco Scarpa, Timothy Whitsett, Landon Inge, Stephen J. Meltzer, Bottiglieri Teodoro, Helen G. Coleman, Lesley A. Anderson, Xin Wang, Ajay Goel^* (0001). A Novel Non-Invasive Circulating Mirna Signature for Detection of Esophageal Adenocarcinoma.

Jinsei Miyoshi^†, Shusuke Toden, Jacob Turner, Feng GAO, Raju Kandimalla, Xin Wang, Mitsuro Kanda, Hideo Baba, Yasuhiro Kodera, Ajay Goel^* (0001). A Novel Mirna-Based, Non-Invasive, Diagnostic Panel for Detection of Esophageal Squamous Cell Carcinoma.

Tsuyoshi Ozawa^†, Feng GAO, Hiroaki Nozawa, Keisuke Hata, Hiroshi Nagata, Daisuke Izumi, Hideo Baba, Xin Wang, Toshiaki Watanabe, Ajay Goel^* (0001). A Novel Mirna Signature for the Detection of Lymph Node Metastasis in Submucosal Colorectal Cancer Patients.

Min-Er ZHONG^†, Du CAI, De-Jun FAN, Wei Wang, Cheng-Hang LI, Ze-Ping HUANG, Qi-Qi ZHU, Min-Yi LV, Chu-Ling HU, Xiaojian Wu, Feng GAO^* (0001). 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.