Research Highlights
AIM Lab focuses on interdisciplinary research in artificial intelligence and medical health, exploring machine learning, deep learning, multimodal data fusion, and intelligent decision-making for medical imaging analysis, clinical data modeling, disease risk prediction, and computer-aided diagnosis.
Medical Imaging Analysis
Focusing on CT, MRI, and other medical imaging data, we study image segmentation, feature extraction, radiomics analysis, and deep learning modeling to explore the value of AI-assisted medical image analysis.
Learn moreClinical Data Modeling
Using structured clinical data, follow-up data, and health-related data, we conduct data cleaning, variable selection, statistical analysis, and machine learning modeling to support disease risk assessment and clinical decision-making.
Learn moreMultimodal Feature Fusion
By integrating medical imaging, clinical indicators, and multi-source medical data, we build multimodal intelligent prediction models to improve the accuracy and stability of disease risk prediction, prognosis assessment, and personalized health management.
Learn moreResearch to Practice
Industry & Applied AI
We connect artificial intelligence research with practical systems, including AI agents, intelligent workflows, deployable tools, and industry collaboration.
AI Agents and Intelligent Workflows
Agent workflows, task orchestration, and domain-focused intelligent assistants for research and practical applications.
Agents, LLMs, workflow orchestration
Applied AI Systems
Turning models into usable tools, prototypes, and decision-support systems designed around real workflows.
Machine learning, multimodal AI, system integration
Collaborative Translation
Working with external partners to explore responsible, technically grounded pathways from research to application.
Prototyping, validation, deployment planning
About the Lab
The AIM Lab at HNFNU focuses on interdisciplinary research in artificial intelligence and medical health, working on medical image analysis, clinical data modeling, multimodal feature fusion, disease risk prediction, and intelligent computer-aided diagnosis. The group emphasizes connecting AI algorithms with real medical problems and exploring machine learning and deep learning methods for medical data analysis and clinical decision support.
The group is guided by research projects and student development. Through literature reading, model reproduction, data processing, algorithm optimization, and results presentation, we help students strengthen research literacy, practical skills, and innovation awareness while building an interdisciplinary and application-oriented AI research team.
Our ValuesCollaboration
The AIM Lab focuses on the intersection of artificial intelligence and medical health and actively pursues open collaboration. We welcome research collaboration and project exchange with universities, research institutes, hospitals, companies, and related teams in medical image analysis, clinical data modeling, multimodal feature fusion, disease risk prediction, intelligent computer-aided diagnosis, and smart health management.
For collaboration inquiries, please contact the group by email. We recommend using the subject line: "AIM Lab Collaboration + collaboration direction / organization name". We look forward to working with researchers and practitioners in related fields to explore the value of AI technologies in medical and health scenarios.
AIM Lab
AIM Lab, Hunan First Normal University
Email: vfeig@hnfnu.edu.cn