Multimodal AI for Medical Imaging and Clinical Decision Support

This special session focuses on artificial intelligence techniques that integrate medical imaging with multimodal clinical data to support accurate diagnosis and clinical decision-making. Topics include multimodal learning, image–text fusion, vision–language models, explainable AI, and AI-driven clinical decision support systems. Research addressing real-world clinical applications and model reliability is particularly encouraged.

Special Session Chair
Dr. Khem Poudel, Middle Tennessee State University, USA

Topics
1. Multimodal medical data fusion
2. Medical image analysis and interpretation
3. Vision–language models for healthcare
4. Image–text and image–signal representation learning
5. Clinical decision support systems
6. Explainable and interpretable AI in medicine
7. Large-scale medical foundation models
8. AI-assisted diagnosis and prognosis
9. Robustness and generalization of medical AI models

Publication
ICBET 2026 IEEE Conference Proceedings, submitted to be archived in IEEE Xplore, indexed by Ei Compendex and Scopus.

Formatting
Each paper is limited to 4-5 pages in double columns including all figures, tables, and references, and additional pages will be charged at 50USD/350CNY per page. Please follow the Conference format.

Formatting Instructions (DOC, LaTeX)
Formatting Instructions (DOC) Abstract

Submission Guideline
Please submit your manuscript via Electronic Submission System (account is needed). (Please remark the session number when you make the submission.)

Important Dates
Submission of Full Papers: 10 Mar. 2026
Notification of Review Result of Papers from Special Sessions: 30 Mar. 2026
Registration Deadline: Apr. 10, 2026