CALL FOR PAPERS

The exponential growth of data generated from various textual sources
presents both a challenge and a huge opportunity. A key challenge lies
in effectively managing and extracting valuable insights from this vast
amount of unstructured and heterogeneous data. To address this issue,
advanced data analytics techniques, ranging from data and text mining to
semantic network analysis and recent advancements in large language
models (LLMs), have become indispensable tools for researchers and
practitioners.
This is particularly relevant in the realm of biomedicine, where text
mining has shown the ability to enable researchers to uncover hidden
patterns, trends, and associations that would otherwise remain buried in
the vast amount of health-related textual data, as research articles,
clinical reports, and electronic health records (EHRs).

On the other hand, semantic network analysis, which focuses on
understanding the structure and dynamics of networks formed by entities
and their interconnections derived from text mining processes, can
facilitate a deeper understanding of the complex interrelationships
within biomedical data. By analyzing properties like centrality,
modularity, and community structures, researchers can identify key nodes
and critical pathways in biological networks, predict disease
associations, and explore the functional organization of biological
systems.
Integrating text mining, semantic network analysis, and large language
models offers a powerful approach to enhance the ability to generate new
hypotheses and insights and support the development of more effective
diagnostics, treatments, and interventions.
The workshop represents an opportunity to explore the latest
advancements in data analytics and text mining in biomedicine. Attendees
will gain insights into developing more interpretable models, handling
large-scale biomedical datasets, and implementing scalable solutions for
real-world healthcare applications.

Moreover, the workshop is highly relevant because it has the potential
to significantly improve the safety, effectiveness, and efficiency of
biomedical interventions through advanced data analytics.

TOPIC OF INTEREST

We invite submissions on a wide range of topics, including but not
limited to:
•       Novel techniques and measures for assessing textual data quality and
handling data integration.
•       Advanced text-mining techniques for biomedical data
•       Construction and analysis of semantic networks in biomedicine
•       Case studies on integrated text mining and semantic network analysis
•       Applications of LLMs in biomedicine
•       Data analytics in precision medicine
•       Text-driven approaches to drug discovery
•       Interpretable or scalable data analytics approaches
•       Application of data analytics and network science in narrative
medicine
•       Computational methods for disease modeling and prediction
•       Ethical considerations in biomedical data analytics
•       Multimodal biomedical data analytics
•       Future trends and challenges in biomedical data analytics

PROGRAM
The workshop will take place on (To Be Announced). The program is not
available yet.

PAPER SUBMISSION –

REGISTRATION AND PUBLICATION

Please refer to socio.org.uk/ddp/

IMPORTANT DATES

Submission of Papers:   June 20, 2025
Notification of Acceptance/Rejection:   July 15, 2025
Camera-ready:   August 10, 2025
Registration:   August 10, 2025
Conference Dates:   August 18-20, 2025
Post-Conference Proceedings Release:   November 30, 2025

WORKSHOP ORGANIZERs

Chiara Zucco, University Magna Graecia of Catanzaro, Italy
Mario Cannataro, University Magna Graecia of Catanzaro, Italy
Marianna Milano, University Magna Graecia of Catanzaro, Italy

PROGRAM COMMITTEE (TO BE CONFIRMED)

Marzia Settino, University of Calabria, Italy
Mario Cannataro, University Magna Graecia of Catanzaro, Italy
Maria Chiara Martinis, University Magna Graecia of Catanzaro, Italy
Giuseppe Agapito, University Magna Graecia of Catanzaro, Italy
Pietro Cinaglia, University Magna Graecia of Catanzaro, Italy
Ilaria Lazzaro, University Magna Graecia of Catanzaro, Italy

Contact: ddp@socio.org.uk