CIBB2026 - Call for Participation: Special Session on AI & Computational Methods in Medical Informatics

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Francesco Branda

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Apr 9, 2026, 11:52:15 PM (9 days ago) Apr 9
to Women in Machine Learning
Dear Colleagues,
We are pleased to announce a Special Session on Artificial Intelligence and Computational Methodologies for Medical Informatics at 21st International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB2026). This session will focus on data-driven approaches that integrate machine learning, data mining, and statistical modeling to extract clinically and biologically meaningful information from heterogeneous biomedical data.
Topics of interest include, but are not limited to:
  • Biomedical and Clinical Data Mining
  • Computational and Predictive Models in Epidemiology
  • Spatiotemporal Analysis of Health and Population Data
  • AI for Clinical Decision Support
  • Predictive Modeling for Disease Progression and Treatment Response
  • Digital Diagnostics and Real-World Clinical Data Analysis
  • Biomedical Text Mining and NLP for Health Applications
  • Multimodal Integration of Clinical, Molecular, and Epidemiological Data
  • Explainable and Interpretable AI in Medical Informatics
  • Scalable Algorithms and Data Infrastructures for Healthcare
  • Public Health Informatics and Surveillance Systems
  • Computational Genomics and Evolutionary Analysis for Medical Informatics
  • Phylodynamic Modeling for Infectious Disease Surveillance
  • AI-assisted Genomic Surveillance in Clinical and Public Health Settings
  • Host–Pathogen Interaction Informatics
  • Integration of Genomic Variability Data into Clinical Decision Support
  • One Health Informatics: Human, Animal, and Environmental Data Integration for Epidemic Intelligence
We warmly invite submissions and participation from researchers working at the intersection of AI, biomedical data, clinical informatics, and public health. This session aims to foster interdisciplinary collaborations and the development of reliable, interpretable, and clinically actionable AI solutions.
We look forward to your contributions and participation!
Best regards,
Francesco Branda 
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