Four tightly coupled engines powering one AI doctor system.
Cognition. Multi-agent orchestration turns evidence into transparent MDT-level decisions.
Perception. Self-supervised multimodal fusion unifies pathology, imaging, and genomics.
Action. From AR navigation to embodied assistance, we turn perception into intervention.
Intuition. Explainable omics modeling reveals the biological “why” behind disease.
Professor
My research leverages AI and big data to improve diagnostics, prognostics, and ultimately, outcomes in cancer and other biomedical fields.
Associate Professor
My research integrates bioinformatics, algorithm development, and data analytics to advance early cancer diagnosis, prognostic stratification, and immunotherapy.
Associate Professor
My research explores the intersection of gastrointestinal endoscopy (GIE) and artificial intelligence (AI), along with the biological mechanisms of colorectal cancer development.
Associate Professor
I have been engaged in the subspecialties of gastrointestinal pathology and breast pathology for more than ten years and am also a senior member of the MDT team.
Dentist
I am a dentist interested in orthodontics and AI-assisted imaging analysis.
Physician
An endocrinologist passionate about artificial intelligence and diabetes, focusing on applying machine learning and bioinformatics to diabetes heterogeneity research.
Surgeon
I am a surgeon focusing on colorectal cancer and translational bioinformatics in clinical practice.
Physician
I am a physician in rheumatology and a current PhD student, focusing on intestinal microecology and host immunity in translational biomedical research.
Postdoc
I focus on leveraging explainable AI and large foundation models to advance medical imaging and digital pathology in colorectal cancer research.
Postdoc
I am a postdoctoral researcher working on AI for colorectal cancer with a focus on clinically actionable models.
Postdoc
My research involves the analysis of brain structure and functional imaging in pituitary adenomas, as well as emotion and cognition.
Research Assistant
I am a research assistant focusing on deep learning, multimodal feature fusion, and medical AI system development.
Research Assistant
I am a research assistant interested in deep learning and medical image analysis for clinical applications.
PhD Student
I am a PhD student at Guangzhou National Laboratory, focusing on colorectal cancer research, biostatistics, and evidence-driven clinical modeling.
PhD Student
I am a PhD student focusing on AI-driven colorectal cancer research and clinically useful model development.
PhD Student
I am a PhD student working on AI methods for colorectal cancer diagnosis and prognosis.
PhD Student
I am a PhD student working on deep learning and medical image analysis for intelligent surgical applications.
PhD Student
I am a PhD student working on AI methods for colorectal cancer research and translational clinical applications.
PhD Student
I am a PhD student studying AI applications in urology, with interests in clinically oriented translational research.
PhD Student
My research leverages AI and big data to improve diagnostics, prognostics, and ultimately, outcomes in colorectal cancer.
Research Student
I am a research student working on AI methods for colorectal cancer analysis and clinical decision support.
Research Student
My research focuses on neoantigen discovery, tumor bioinformatics, and the development of bioinformatics databases.
Research Student
My research focuses on neoantigen discovery, tumor bioinformatics, and the development of bioinformatics databases.
Research Student
Wen DONG is a master's student in Dermatology. She is pursuing her degree at the Sixth Affiliated Hospital of Sun Yat-sen University. She is now interested in studying genetic skin diseases.
Research Student
I work at the intersection of AI and genodermatoses, focusing on multimodal large language models for skin cancer screening and diagnosis in rare inherited skin diseases.
† First or co-first author, * Corresponding or co-corresponding author, bold names are lab members
Our lab publicly released MedAutoScience on GitHub on March 29, 2026. It is an agent-first, human-auditable platform for progressing disease-focused medical studies from versioned …
Our team published INTELCAPE in Clinical Gastroenterology and Hepatology, an AI system for automated capsule endoscopy analysis that supports faster and more accurate Crohn’s …
Our team published MotifCC in Cancer Letters, a multi-omics immune classification framework for colorectal cancer that links tumor heterogeneity to prognosis and immunotherapy …
Our lab’s in-house large language model platform officially went live on March 12, 2026, and is now available to all lab members. The platform provides unlimited access to GPT 5.4 …
Medical AI Lab
The Sixth Affiliated Hospital of Sun Yat-sen University
4th Floor, Phase IV, Building M3
Guangzhou International Bio Island
Guangzhou, Guangdong
For collaborations, student inquiries, and lab visits.