1. AI Agents in Digital Health and Medicine
Advances in Computational Intelligence (CI) and autonomous systems are enabling a new generation of AI agents capable of perceiving, reasoning, and acting within digital health and clinical environments. AI agents and multi-agent systems are accelerating innovation in health and medicine by enabling clinical decision-making, autonomous health monitoring, multimodal medical assistants, and integrating adaptive intelligence directly into clinical workflows. Despite these opportunities, the deployment of AI agents in healthcare and medicine is challenged by heterogeneous data sources, limited interoperability, and concerns about model reliability, including hallucinations, bias, privacy risks, and the safety of autonomous actions. Ensuring trustworthy, clinically aligned behavior requires rigorous evaluation, transparent reasoning, and frameworks that support human oversight. This special session aims to explore advances in health research and clinical practice driven by autonomous agents, agent-based workflows, and next-generation CI models, focusing on the application of Intelligent Agents in digital health, precision medicine, bioinformatics, clinical decision-making, drug discovery, and biomedical engineering. The goal is to bridge the gap between computational intelligence researchers and clinical experts from multidisciplinary backgrounds, fostering collaboration and cross-domain innovation.
Website
https://mamatjanlab.com/IEEE-CIBCB-2026
Organizers
- Dr. Yasin Mamatjan, Chair, Associate Professor, Thompson Rivers University, BC, Canada, (Visiting Scientist, Princess Margaret Cancer Centre, Toronto, Canada). Email: ymamatjan@tru.ca
- Dr. Arvind S. Mer, Assistant Professor, Faculty of Medicine and School of Electrical Engineering & Computer Science, University of Ottawa, Canada. Email: amer@uottawa.ca
- Dr. Alvaro David Orjuela-Cañón, Universidad del Rosario, Colombia.
2. Ethical and Interpretable Representations in Computational Bio-Medicine
In the bio-medical domain, many complex computational tasks require advanced, novel, and far from trivial representations, to either mitigate or provide a clearer overview of the problem under investigation. On top of that, the rapid adoption of Machine Learning, Generative and Deep Learning models in high-risk domains means that representational choices directly influence not only the accuracy of the outcomes but also the ethical accountability and safety of the resulting AI systems. Although several techniques – ranging from generative and self-adaptive representations to search space manipulation – can improve the efficiency of optimization methods and the accuracy of machine learning models, they can also hamper transparency and make the decision process more convoluted, obscure the algorithmic bias, reduce the interpretability, and complicate legal accountability. The objective of this special session is to bring together technical experts, ethical, and legal experts in a dedicated forum to discuss the role of representation in Computational Intelligence. We invite researchers who focus on representation as a central mechanism for promoting trustworthy, fair, and interpretable Computation Intelligence. We welcome both technical papers addressing the human, and legal dimensions of AI, and non-techincal papers focusing on the ethical side of leveraging CI in the bio-medical domain.
Website
https://matteograzioso.com/special-session-eircbm-cibcb2026
Organizers
- Dr. Daniele M. Papetti (IEEE CIS ARBM TF Chair), University of Milano-Bicocca, Italy.
- Matteo Grazioso (IEEE CIS ARBM TF Member), Ca’ Foscari University of Venice, Italy.
- Prof. Tayo Obafemi-Ajayi (IEEE SHIELD TC Chair), Missouri State University, USA.
- Prof. John W. Sheppard (IEEE SHIELD TC member), Montana State University, USA.
3. Precision AI and Technological Healthcare Informatics (PATH-I)
As Artificial Intelligence (AI) drastically reshapes industries globally, its impact on precision healthcare and informatics is vital. Moving beyond traditional approaches, AI facilitates faster and more accurate diagnostics, optimized treatment plans, and intelligent healthcare management, consequently enhancing patient outcomes and quality of care. This special track aims to bring together researchers, clinicians, data scientists, and industry experts to present and discuss the latest research in AI-powered healthcare systems. The session focuses on the structural and computational foundations of medical intelligence, from deep learning in medical imaging to predictive modeling for disease detection.
Website
https://httpspath-icomieee-cibcb-2026.com/
Organizers
- Prof. Nabeel AL Yateem, University of Sharjah, UAE.
- Dr. Samia Kouki, Higher Colleges of Technology, UAE.
- Dr. Nacim Yanes, University of Gabes, ISGGB, and UMA, RIADI, Tunisia.
- Dr. Malika Charrad, University of Paris-Pantheon-Assas, France.
4. Governance-Aware and Sustainable Computational Intelligence for Medicine and Digital Health
This special session focuses on governance-aware and sustainability-driven computational intelligence architectures for bioinformatics, biomedical engineering, and healthcare informatics. We invite contributions that connect algorithmic design, model interpretability, energy efficiency, privacy- preserving learning, and ethical deployment frameworks. The goal is to foster interdisciplinary dialogue between CI researchers, health informaticians, bioengineers, and policy-aware AI designers, advancing trustworthy and sustainable biomedical AI systems.
Website
ΤΒΑ
Organizers
- Polat Goktas, Sabanci University, Türkiye
- Elif Calik, University of Galway, Ireland
- Malika Bendechache, University of Galway, Ireland