held in conjunction with 39th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2026)

Limassol, Cyprus

June 03-05, 2026

https://2026.cbms-conference.org/

CALL FOR PAPER

Workshop on Green-Aware Artificial Intelligence for Network and Text Mining in Computational Biology and Medicine

(GreenAI-NetText Workshop)

The healthcare domain is rapidly evolving through the adoption of advanced computational methods. Alongside the quest for accuracy and interpretability, there is now an increasingfocus on energy efficiency and environmental sustainability of AI algorithms. On one side,

green-aware and interpretable machine learning are becoming crucial to ensure that models used in clinical practice are not only accurate, transparent, and trustworthy, but also optimized to reduce computational costs and energy consumption. On the other side, network science, pathway-based analysis, and biomedical text mining provide powerful frameworks to capture the complexity of biological systems and biomedical knowledge, from gene and protein interactions to drug–target–disease relationships and from scientific publications to clinical reports, ultimately supporting translational research and therapeutic innovation. Green-aware AI brings together serverless computing, edge computing, and data reduction strategies to minimize energy consumption. Applied to multilayer biological networks and biomedical text corpora, it has the potential to significantly reduce computational and environmental costs while preserving analytical power.

Program Interest to the CBMS Community

The workshop is highly relevant to the CBMS community due to its direct implications for enhancing the sustainability, safety, effectiveness, and efficiency of biomedical interventions through advanced computing. It addresses the growing demand for AI systems in medicine

to be transparent in their functionality, accurate in their predictions, and responsible in their resource consumption. Biological Network Analysis can be utilized in several applications such as the identification of drug targets, determining the role of proteins or genes of unknown function, the design of effective strategies for infectious diseases, and the early diagnosis of neurological disorders through the detection of abnormal patterns of neural synchronization in specific brain regions. Text Mining approaches (topic modeling, named entity recognition, sentiment and polarity

detection) can be used to extract knowledge from bioinformatics publications, medical reports, and patient questionnaires. Providing green-aware versions of these methods may have a great scientific and environmental impact, especially when combined with multilayer network analysis.

The main motivation for the workshop is to collect advanced works on the development of new green-aware pipelines, algorithms, and tools for the network and text analysis of complex systems in different domains. The workshop also seeks original research papers presenting applications of parallel, serverless and high-performance computing to biology

and medicine.

After the workshop, selected high-quality contributions will be invited to submit extended versions of their work to a Special Issue that will appear in the Journal of Computational Science (Elsevier) — a journal ranked Q1 in recent years according to both Scimago and Web of Science.

Topics of Interest

· Green-aware and interpretable ML models in healthcare

· Serverless and edge-computing architectures for biomedical AI

· Foundations of causal inference and its application in multi-omic data

· Innovations in Explainable AI (XAI) for clinical decision support systems

· Graphical models for causal discovery and their use in biological networks

· Integration of multi-omic data for causal analysis and pathway discovery

· Green-aware graph embedding, network alignment and representation learning

· Network-based bioinformatics methods and modeling of complex diseases

· Multilayer and heterogeneous network analysis for disease–drug–gene relationships

· Parallel and energy-efficient algorithms for large-scale biomedical networks

· Green-aware text mining: topic modeling, named entity recognition, polarity/sentiment

detection on biomedical texts

· Lexicon-based, rules-based, and ML-based text mining with low-power consumption

· Applications of green-aware AI to social networks, infrastructure, transportation and

cybersecurity

PAPER SUBMISSION, REGISTRATION AND PUBLICATION

Submission Link:

 https://easychair.org/conferences/?conf=ieeecbms2026.

IMPORTANT DATES

• Paper submission deadline: February 20, 2026 (AoE)

• Notification of acceptance: April 10, 2026

• Camera-ready due: April 24, 2026

WORKSHOP ORGANIZER

Marianna Milano, University Magna Graecia of Catanzaro, Italy

m.milano@unicz.it

Giuseppe Agapito, University Magna Graecia of Catanzaro, Italy

agapito@unicz.it

Chiara Zucco, University Magna Graecia of Catanzaro, Italy

chiara.zucco@unicz.it 

PROGRAM COMMITTEE (TO BE CONFIRMED)

•  · 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

  • · Loris Belcastro, University of Calabria, Italy

  • · Anna Bernasconi, Politecnico di Milano, Italy

  • · Chiara Pastrello, Krembil Research Institute (KRI), Canada

  • · Antonio Guerrieri, ICAR-CNR, Italy

  • · Davide Chicco, University of Toronto, Canada

  • · Pietro Pinoli, Politecnico di Milano, Italy

  • · Luigi Alfonso, University of Calabria, Italy

  • · Giuseppe Fedele, University of Calabria, Italy

  • · Mariamena Arbitrio, CNR, Italy

  • · Francesca Scionti, CNR, Italy

  • · Paola Lecca, University of Bozen-Bolzano, Italy

  • · Zeeshan Abbas, Jeonbuk National University, South Korea

  • · Luca Barillaro, University Magna Graecia of Catanzaro, Italy