Special Session at IEEE CIBCB 2026

Special Session:

Precision AI and Technological Healthcare Informatics (PATH-I)

Bioinformatics Clinical AI Trustworthy Systems

2026 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2026) Conference Website

31 August – 2 September 2026 · Athens, Greece

Important Dates

  • 📄 Extended Submission: Mar 31, 2026 Apr 20, 2026
  • 🔗 Submission Link: Submit Your Paper Here
  • 📬 Notification: May 31, 2026
  • ✅ Final Paper: Jun 30, 2026
  • 📍 Conference: 31 Aug – 2 Sep 2026

Special Session Abstract

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.

Special Session Chairs

Prof. Nabeel Al Yateem
Prof. Nabeel AL Yateem

University of Sharjah, UAE

Email: nalyateem@sharjah.ac.ae

Dr. Samia Kouki
Dr. Samia Kouki

Higher Colleges of Technology, UAE

Email: skouki@hct.ac.ae

Dr. Nacim Yanes
Dr. Nacim Yanes

University of Gabes, ISGGB, Tunisia / UMA RIADI (LR99ES26), Tunisia

Email: Nacim.yanes@ensi-uma.tn

Dr. Malika Charrad
Dr. Malika Charrad

University of Paris-Panthéon-Assas, France

Email: malika.charrad@efrei.fr

Chair Biographies

Prof. Nabeel AL Yateem is Professor and Chair of the Nursing Department at the College of Health Sciences, University of Sharjah, and Adjunct Professor at Charles Sturt University, Australia. He holds a Ph.D. in Children and Adolescents Health Nursing from the University of Galway, Ireland. His research has been supported by grants from the Irish Hospice Foundation, Al Jalila Foundation, and the University of Sharjah. He also serves on the editorial boards of journals including the Scandinavian Journal of Caring Sciences and the Journal of Pediatric Nursing. His work reflects a strong commitment to advancing nursing practice, education, and global research collaboration. Prof. Al-Yateem has extensive experience in pediatric health, research, and education.

Dr. Samia Kouki is a faculty member and researcher at the Higher Colleges of Technology (HCT), UAE. Her work focuses on artificial intelligence, cloud computing, and digital transformation, with a strong emphasis on applied AI systems for healthcare, education, and sustainability. She is actively involved in interdisciplinary research that bridges computational intelligence with real-world problem domains, including AI-driven clinical decision support, data-driven healthcare informatics, and responsible AI deployment. Dr. Kouki has published in several international journals and conferences and contributes to academic–industry collaborations aimed at translating research into scalable, impactful solutions.

Dr. Nacim YANES is an Assistant Professor of Computer Science Applied to Management and a research member of the RIADI Laboratory at the National School of Computer Sciences (ENSI), University of Manouba, Tunisia. He is currently a faculty member at the Higher Institute of Management of Gabes (ISGGB), University of Gabes. From 2017 to 2022, Dr. Yanes held a faculty position at Jouf University, Saudi Arabia. During this period, he also served as Program and Quality Coordinator for the Information Systems program, where he chaired the ABET and NCAAA accreditation committees and played a key role in quality assurance and curriculum development. He holds a Master’s degree from the Higher Institute of Management of Tunis (ISG-Tunis) and a Ph.D. in Computer Science from ENSI. His research interests include AI & Machine Learning, Recommender Systems, Educational Technologies & Serious Games, Semantic Data & Intelligent Information Systems, and Software Engineering Tools and Support Systems. An active mentor and researcher, Dr. Yanes co-supervises several Ph.D. and Master’s theses and has published widely in reputable international journals and conference proceedings.

Dr. Malika Charrad is an Associate Professor of Computer Science and the Head of the Data & AI Program at EFREI Paris- Université Paris-Panthéon-Assas, France. She received her Ph.D. in Computer Science from Conservatoire National des Arts et Métiers (CNAM, Paris), in collaboration with INRIA Rocquencourt (France) and École Nationale des Sciences de l’Informatique (ENSI, Tunisia). She subsequently conducted postdoctoral research at Laval University, Canada. Her research focuses on Artificial Intelligence, with particular emphasis on Automatic and Incremental learning, Knowledge Graphs, Explainable AI (XAI), and Data-driven Decision-making, with applications in eSports analytics and Healthcare systems. She is actively involved in the scientific community as an author and reviewer for numerous high-impact international journals and conferences.

Special Session Tracks

AI for Medical Imaging & Diagnostics

Exploring AI-driven techniques for medical image analysis, computer-aided diagnosis, and intelligent imaging systems to support faster and more accurate clinical decision-making.

Predictive Modeling & Clinical Decision Support

AI models and decision support systems for disease risk prediction, prognosis, personalized treatment planning, and data-driven clinical workflows.

Trustworthy, Explainable & Privacy-Preserving AI

Methods for explainable AI, fairness, robustness, federated learning, and privacy-preserving architectures to enable secure and ethical deployment of AI in healthcare systems.

Computational Intelligence in Bioinformatics

Computational intelligence techniques for genomics, proteomics, systems biology, drug discovery, and biomedical data mining.

Real-World Healthcare Data Applications

Practical deployment of AI using real-world healthcare data, including EHR analytics, clinical NLP, population health surveillance, and operational optimization in hospitals.

AI for Personalized & Precision Medicine

AI-driven approaches for personalized treatment planning, patient stratification, multi-modal data fusion, and precision medicine, enabling tailored therapies and improved patient outcomes.

Program Committee

Program Committee members for the Special Session: Precision AI and Technological Healthcare Informatics (PATH-I)

Prof. Wadii Boulila
Prince Sultan University, KSA
Prof. Nor Shahriza Abdul Karim
Prince Sultan University, KSA
Prof. Mondher Maddouri
University of Paris-Panthéon-Assas, France
Dr. Heba Khalil
University of Sharjah, UAE
Dr. Fatma Ahmed
University of Sharjah, UAE
Dr. Mano Joseph Mathew
Université Paris Panthéon-Assas, France
Dr. Ilyes Jenhani
University of Doha for Science and Technology, Qatar
Dr. Lilia Sfaxi
University of Carthage, Tunisia
Dr. Thompson Stephan
Gulf Medical University, UAE
Dr. Amar Ahmad
New York University, UAE