A proposed special session at

International Joint Conference on Neural Networks (IJCNN) @ WCCI 2026

 Maastricht, the Netherlands · 21 –  26 June, 2026

The ongoing transformation driven by Artificial Intelligence (AI) stems from the convergence of multiple technologies—such as machine learning, deep learning, natural language processing, computer vision, and, more recently, generative and agentic AI. Together, these technologies are reshaping how knowledge is created, analyzed, and applied across sectors, with particularly profound implications in healthcare. In this field, AI enables the integration and analysis of vast and complex data sources—including electronic health records, administrative data, biometric indicators, sensor outputs, and medical imaging—transforming them into actionable insights that enhance clinical decision-making and improve health outcomes.

A particularly transformative development is the rise of generative and agentic AI. Generative AI offers new opportunities to accelerate drug discovery, synthesize and analyze medical images, generate synthetic data for research, and enhance patient–clinician communication through intelligent assistants. Meanwhile, agentic AI systems—capable of reasoning, planning, and autonomously executing tasks toward defined goals—have the potential to optimize workflows, support clinical decision-making, and increase efficiency in healthcare delivery. However, these advancements also introduce new ethical, technical, and governance challenges, such as ensuring the reliability and accountability of autonomous systems, preventing misinformation or data fabrication, addressing bias, and protecting patient privacy.

Despite this progress, the broader integration of AI in healthcare continues to face persistent challenges, including low-quality training data, model opacity, algorithmic bias, and privacy concerns. Addressing these issues is essential for achieving responsible, transparent, and equitable AI adoption in healthcare systems worldwide.

This special session seeks to highlight the latest progress in applied, generative, and agentic AI for healthcare, focusing on innovative solutions to emerging challenges and the development of reliable, trustworthy, and human-centered intelligent systems. It will serve as a global forum for researchers and practitioners to exchange knowledge, share experiences, and discuss advancements that enable patient-focused, data-driven, and sustainable healthcare transformation through AI.

List of Topics

Contributions are expected to be related, but not limited, to the following topics:

• Responsible Generative AI for Healthcare Innovation and Discovery

• Ethical and Responsible Agentic AI for Safe Healthcare Automation

• AI-driven medical decision support 

• Biomedical and health informatics 

• Computer-aided disease detection, diagnosis, and prognosis 

• Public health informatics 

• Explainable AI in healthcare 

• Fuzzy modeling for intelligent healthcare 

• Advanced neural network architectures in healthcare applications

• Transfer learning, multitask learning and multi-view learning in healthcare 

• Machine learning and deep learning-driven approaches for medical imaging, ECG, EMG, EEG data, etc.  Natural language processing in medical science

• Real-time neural networks for patients monitoring

• Privacy-aware AI architectures in healthcare, including decentralized approaches (e.g. federated learning)

Audience

This special session is intended for students, scientists, professionals, and practitioners in the field of machine learning (ML) and deep learning (DL) approaches in medicine and healthcare. The special session has an emphasis on the theoretical and practical implementations and implications of the ML and DL approaches, specifically on addressing key challenges and issues for delivering reliable and trustworthy intelligent systems in healthcare and medicine. Hence a broad range of stakeholders are invited to participate, including academia, healthcare professionals, researchers, pharmaceutical industry, the EU-Innovation Network, and related entities.

Keywords– Educational, technical, industrial, and practical communities on trustworthy AI, explainable AI, ethical-by-design, AI in medicine, and AI in healthcare are welcome.

Submission Guidelines

All submissions have to be adhered to the general author guidelines provided by IJCNN here. 

Once you are in the submission system, select the Special Session (AI in Healthcare: Harnessing Emerging, Generative and Agentic Technologies for Responsible Innovation) as the main topic of your paper.

This year, the review process will be double-blind, i.e. reviewers will not know the authors' identity (and vice versa). Authors should ensure their anonymity in the submitted papers.

The accepted papers will be included in the proceedings of the IJCNN 2026 and indexed in IEEEXplore.

Important Dates

• Paper submission: January 31, 2026 

• Notification of acceptance: March 15, 2026

• Final paper submission: TBA

• Special session @ IJCNN: TBA

Special Session Organizers

Lourdes Martínez-Villaseñor (chair), Universidad Panamericana, Mexico
Hiram Ponce, Universidad Panamericana, Mexico
Lerina Aversano, University of Foggia, Italy
Mario Luca Bernardi, University of Sannio, Italy
Rui Chen, Samsung, United States of America
Kai Qin, Swinburne University of Technology, Australia

Contact

Any inquiries or doubts, please refer to Lourdes Martínez-Villaseñor <lmartine@up.edu.mx>.

This special session is intented to be co-located at the IJCNN-WCCI 2026. More information can be found in the official website of the conference: https://attend.ieee.org/wcci-2026/