CALL FOR PAPERS
The workshop aims to bring together researchers and practitioners working at the intersection of text mining, clinical natural language processing (NLP), and trustworthy AI, with a particular focus on healthcare applications. As clinical and biomedical text mining becomes central to decision support, patient stratification, and knowledge discovery, new challenges emerge: ensuring privacy, robustness, interpretability, fairness, and regulatory compliance. This workshop will provide a platform to discuss novel solutions for deployable and ethically-aligned clinical NLP systems, especially in privacy-sensitive and low-resource medical domains. We also welcome contributions that explore the integration of clinical texts with other modalities (e.g., imaging, structured EHR data, genomics) when grounded in privacy-preserving and interpretable frameworks. In particular, we encourage critical and applied perspectives on the use of large language models (LLMs) in clinical and biomedical text mining, with attention to privacy risks, explainability challenges, domain adaptation, and sustainability.
TOPIC OF INTEREST
We invite submissions on a wide range of topics, including but not limited to:
Privacy-preserving and secure text mining in clinical and biomedical domains
De-identification, anonymization, and re-identification risk mitigation in health data
Federated and distributed learning for sensitive text data
Domain adaptation, generalizability, and robustness in clinical NLP systems
Bias detection, fairness, and equity in healthcare language models
Explainable and interpretable models for clinical decision support
Biomedical knowledge-driven NLP
Synthetic text generation for privacy, training, and data augmentation
Efficient and sustainable NLP architectures for real-world healthcare settings
Temporal and longitudinal modeling of patient trajectories from clinical narratives
Compliance-aware NLP aligned with regulatory frameworks (e.g., GDPR, HIPAA)
Multimodal learning combining text with imaging, structured data, or omics
Evaluation and mitigation of risks in large language models applied to healthcare
Retrieval-augmented and knowledge-grounded generation for clinical tasks
Adaptation and tuning of foundation models in low-resource or clinical domains
Causal reasoning and hypothesis generation from clinical text
PROGRAM
The workshop will take place on (To Be Announced). The program is not available yet.
PAPER SUBMISSION, REGISTRATION AND PUBLICATION
Please submit a full-length paper (up to 8 page IEEE 2-column format) through the online submission system (you can download the format instruction here:
http://www.ieee.org/conferences_events/conferences/publishing/templates.html
Electronic submissions (in PDF or Postscript format) are required. Selected participants will be asked to submit their revised papers in a format to be specified at the time of acceptance.
IMPORTANT DATES
Submission of Papers: October 15, 2025
Review and Notification: November 10, 2025
Camera-ready: Novembre 23, 2025
Workshop Date: TBA
WORKSHOP ORGANIZER
Chiara Zucco, University Magna Graecia of Catanzaro, Italy
Maria Chiara Martinis, University Magna Graecia of Catanzaro, Italy
Mario Cannataro, University Magna Graecia of Catanzaro, Italy
PROGRAM COMMITTEE (TO BE CONFIRMED)