An accepted special session at

International Joint Conference on Neural Networks (IJCNN) 

Rome, Italy · 30 June – 5 July, 2025

The emergence of the big data era in healthcare has led to the widespread collection of health information in various forms, including electronic patient records, administrative claims data, biometric data, sensor data, and medical images. Artificial Intelligence (AI) and machine learning techniques are increasingly being employed to extract valuable insights from this complex data, transforming it into actionable knowledge that supports improved healthcare decision-making and outcomes.

However, significant challenges remain in the application of AI within healthcare. Practical issues like low-quality training data, the opacity of AI models (black box problems), algorithmic bias and fairness concerns, and data privacy risks pose barriers to the effective integration of AI into existing healthcare systems. Addressing these challenges is crucial for AI to achieve broader adoption and meaningful impact in transforming healthcare.

This special session aims to present recent advancements in applied AI, focusing on solutions to emerging challenges and the development of reliable, trustworthy intelligent systems in healthcare and medicine. It will also serve as a global platform to share and discuss the latest research aimed at delivering patient-centered, outcome-driven, and effective healthcare through the use of AI.

List of Topics

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

• 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 (Trustworthy and Reliable Artificial Intelligence Applications in Healthcare Decision-Making) 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 2025 and indexed in IEEEXplore.

Important Dates

• Paper submission: January 15, 2025 

• Notification of acceptance: March 31, 2025

• 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 co-located at the IJCNN 2025. More information can be found in the official website of the conference: https://2025.ijcnn.org/