The Third IEEE International Conference on Medical Artificial Intelligence (IEEE MedAI 2025)
TOPICS
Areas in Medicine & Healthcare Benefited from AI (MH)
Area 1: Infrastructure of Medicine
- Medical record database and data linkage
- Software, hardware, robotics and languages for medicine
- Drug design, development and clinical use
- IoT infrastructure, software and methods for patients' communication
- Ethics, privacy and security of managing and using patients' data
- Ethics, privacy and security of medical decision making
Area 2: Telemedicine
- Remote diagnosis
- Remote consultation
- Remote operation
- Remote treatment planning
- Remote monitoring, recommendation and intervention
Area 3: Digital and Precise Medicine
- Digital hospital and digital health care
- Distributed digital medicine
- Virtual reality in medicine
- Augmented reality in medicine
- Automated control of medical facilities and devices
- Multi-modal medical image processing and interpretation
- 3D image reconstruction
Area 4: Automated Medicine
- Automated interpretation of medical records
- Automated synthesis of patients' data
- Automated decision making of diagnosis
- Automated recommendation for medical services
- Automated generation of prescription
- Automated recommendation of treatment plan
- Assistive living
- Computerized clinical consultation, discussion and argumentation
- Disease predisposition, diagnosis, progression and treatment
Area 5: Precise Medicine and Biomedical Informatics
- Medical data, including blood chemistry, biomarkers, analyses and interpretation
- Precise surgery and plan-guided plastic medicine
- Individualized medicine
- Targeted medicine
- Particular patients adapted immunotherapy
- Cellular/molecular data analyses and interpretation
- Detection, qualification and annotation of genomic variants
- Disease-omic data relationship knowledge base construction
- Epigenetics and chromatin structure
- Pharmacogenomics
- Cancer genomics
Area 6: Computational Systems Biology
- Immune system modeling
- Single-cell and spatial omics
- Biomolecular structure and function prediction
- Interpretation of patient genomic, transcriptomic and omic data
- Disease onset, development modeling
- Microbe-human interactions
- Metabolic reprogramming in diseases
- Complex multi-component interactions within biological systems
- Gene regulation and circuit design
- Network biology and medicine
Areas in AI for Medicine and Healthcare (AI)
Area 1: Infrastructure and Knowledge-based AI
- Algorithms, software and system architecture
- Hardware and performance
- Programming Languages
- Knowledge representation and reasoning
- Knowledge graphs, ontologies and platform and tools
- Knowledge-based natural language understanding
- Knowledge-based systems in general
- Infrastructure supporting mobile and distributed AI
Area 2: Bionic AI
- Swarm AI
- Neural Network based AI
- Deep learning supported AI
- Neural-symbolic integrated AI
- Non-Euclidean geometry and deep learning
- Geometric flow learning
- Brain-like Intelligence
Area 3: Collective AI
- Federated AI
- Crowd AI
- Digital Twins
- Distributed AI
- Game theory-based AI
- Consultation in decision making
- Negotiation in decision making
- Argumentation in decision making
- Computer vision and image processing
Area 4: Automated AI
- Automated decision making
- Automated process design
- Mathematics inspired AI
- Nature inspired AI
- Situation inspired AI
- Metaverse based AI
- AI-inspired algorithms
- Automated monitoring, recommendation and intervention
Area 5: Generative AI
- Generative adversarial network
- Automated crowd intelligence generation
- Automated language, image, voice and video generation
- Automated scientific theory generation
- Automated algorithms generation
- ChatGPT-like AI
- Generative AI with on-chip synthesis
- Quantum AI
Area 6: Trustworthy AI
- Explainable AI
- Causality preserving AI
- Ethical AI considerations
- Deep reasoning and big data processing
- Privacy preservation in medical data
- Data security of AI
- Cybersecurity of AI
- Trust and transparency in AI
- Social implications of AI technologies
- AI Responsibility, bias and user needs
We particularly encourage submissions in emerging topics of high importance such as ethical data analytics, automated data analytics, data-driven reasoning, interpretable modeling, modeling with evolving environments, multi-modal data mining, and heterogeneous data integration and mining.