Call for papers now open: Synthetic Healthcare Data Generation and Clinical Decision Support workshop at IEEE CBMS 2026

27 of November of 2025

Call for papers now open: Synthetic Healthcare Data Generation and Clinical Decision Support workshop at IEEE CBMS 2026

The SEARCH project has organised a special track workshop at the 39th IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS 2026), that will take place from 3rd to 5th of June in Limassol, Cyprus.

The workshop ‘Synthetic Healthcare Data Generation and Clinical Decision Support Systems’ aims to bring together professionals from multiple disciplines working in this research field. It provides a forum to showcase state-of-the-art methods, discuss emerging challenges, and highlight how synthetic data is shaping the future of clinical decision support systems and healthcare innovation.

SEARCH is now calling for full papers focused on the generation, validation, and translational application of synthetic data for clinical decision support systems. The project is especially interested in novel synthetic data generation models applied to diverse clinical data modalities including—but not limited to— electronic health records (EHRs), biosignals (e.g., ECG, EEG, PPG) radiological images (e.g., CT, MRI), endoscopic images, and histopathological as well as genomic data. The track also welcomes contributions presenting innovative methods or metrics for assessing synthetic data, particularly those examining aspects such as quality, credibility, fidelity, utility, diversity, and privacy.

Topics of this special track include (but are not limited to):

  • Advanced generative models
  • Multi-modal data synthesis
  • Conditional, controllable and counterfactual generation
  • Data efficient generative models
  • Foundational models
  • Explainable / interpretable synthetic data generation
  • Techniques for generating data for rare conditions and underrepresented groups
  • Fair data generation and decision-making
  • Synthetic data in the context of personalised medicine
  • In-silico testing and validation of CDS tools on synthetic patient cohorts
  • Privacy-preserving synthetic data
  • Data homogenisation techniques for multisource learning models
  • Federated learning for synthetic data generation
  • Synthetic data evaluation metrics
  • Standards, regulatory and ethical frameworks
  • Synthetic datasets and clinical utility

All submissions will undergo a rigorous peer-review process. The full paper submission is open until the 20th of February.

Click on this link for further information and application details