1st Workshop on Artificial Intelligence for Biomedical Data (AIBio) 2025
Held in conjunction with the 28th European Conference on Artificial Intelligence (ECAI) 2025
25-26 October 2025, Bologna, Italy

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About the workshop

AIBio 2025 explores the transformative role of artificial intelligence (AI) in biomedical research, with a focus on medical imaging, multi-omics, clinical data, and digital health. Biomedical data is inherently complex, characterized by heterogeneity, high dimensionality, and scalability challenges, making it difficult to extract meaningful insights. AI provides powerful tools to address these challenges, driving breakthroughs in disease diagnostics, personalized treatment strategies, and healthcare efficiency.

This workshop emphasizes pathology and omics data, where AI has demonstrated immense potential in disease understanding, molecular profiling, and tissue analysis. However, AIBio 2025 also broadens its scope to include translational medicine, digital health, and the role of telecommunications technologies in biomedical AI. This includes advancements in AI-driven telemedicine, edge and cloud computing for biomedical data analysis, 5G/6G applications in digital health, and secure AI models for biomedical data over networks, enabling real-time diagnostics, remote patient monitoring, and scalable healthcare solutions.

AIBio 2025 also emphasizes the ethical considerations and interpretability of AI models in clinical settings, focusing on strategies to mitigate biases related to gender, ethnicity, and age through fair machine learning techniques. Ensuring that AI systems are transparent, interpretable, and equitable is vital for their integration into healthcare practices.

Workshop Objectives

  • Present cutting-edge AI innovations in biomedical applications
  • Discuss key challenges in multi-modal data integration
  • Explore the impact of telecommunications technologies on AI-driven healthcare
  • Foster collaborations to advance AI-powered biomedical research and digital health solutions
  • Address ethical considerations and interpretability of AI models in healthcare applications

By bringing together experts from diverse fields, AIBio 2025 aims to bridge the gap between AI research, telecommunications, and real-world medical applications, driving practical and impactful advancements in healthcare.

Call for Papers

The AIBio 2025 workshop invites researchers, clinicians, data scientists, and industry professionals to submit their latest findings on AI-driven biomedical research. We seek high-quality, original contributions addressing AI applications in biomedical data, including but not limited to:

  • AI for digital pathology and whole-slide imaging
  • Machine learning for multi-omics data integration
  • Deep learning in clinical and biomedical imaging
  • Computational pipelines for multi-modal biomedical data
  • Federated learning, privacy, and security in biomedical AI
  • AI-driven biomarker discovery and precision medicine
  • Challenges in translating AI research into clinical practice
  • AI-driven telemedicine and remote patient monitoring
  • Edge and cloud computing for biomedical AI applications
  • 5G/6G and telecommunications technologies for AI-powered healthcare
  • Ethical considerations and interpretability of AI models in clinical settings – Strategies to mitigate biases related to gender, ethnicity, and age using fair machine learning techniques

Submission Guidelines

Authors must submit original, unpublished research contributions in English, formatted according to the Springer Communications in Computer and Information Science (CCIS) series guidelines. Manuscripts should be prepared using the official Springer LaTeX or Microsoft Word templates, available at Springer’s Author Guidelines.

Authors can submit papers in the following categories:

  • Full Research Papers (12-14 pages, including references) These papers should present original, substantial, and unpublished research contributions, including theoretical advances, novel methodologies, experimental studies, or well-founded algorithmic approaches. The research should be clearly motivated, and its significance and relevance should be demonstrated through a thorough evaluation and comparison with state-of-the-art techniques.
  • Short Papers (6-8 pages, including references) Short papers should describe preliminary research results, ongoing work, or innovative ideas with initial findings. These submissions may include early-stage research that introduces a new concept, proposes a novel hypothesis, or presents a compelling but incomplete dataset or methodology.

Submission Process

Authors must submit their manuscripts electronically in PDF format via the official submission system: Chairing Tool AIBio2025.

Double-Blind Review

The review process follows a double-blind policy, meaning that:

  • Authors must anonymize their submissions by removing any identifying information, including names, affiliations, and acknowledgments.
  • Self-citations should be written in the third person (e.g., instead of “In our previous work [1], we proposed…”, write “In previous work [1], a method was proposed…”).
  • Supplementary materials should also be anonymized.

Each paper will be subject to a rigorous peer-review process by at least three experts in the field. Papers will be evaluated based on the following criteria:

  • Originality: The contribution should be novel and advance the state of the art.
  • Technical Quality: The methodology should be sound, and results should be well-supported.
  • Clarity: The paper should be well-structured and clearly written.
  • Relevance: The submission should align with the conference/workshop topics.

Authors must ensure that their papers do not contain plagiarized content or overlapping submissions to other venues. Papers that do not comply with the formatting, length, or anonymization requirements will be rejected without review.

Registration

The AIBio workshop registration policy follows that of the main ECAI conference. Details can be found https://www.ecai2025.eu/registration.

To attend the AIBio workshop, at least one author of each accepted paper is required to register for the ONLY WEEKEND option by the early registration deadline. Authors also have the option to register for the ECAI main conference + WEEKEND. However, please note that registering solely for the ECAI main conference does not grant access to the AIBio workshop.

Presentation

At least one author of each accepted paper must register for ONLY WEEKEND or ECAI main conference + WEEKEND by early registration deadline, and present their work at the workshop. The presentation is a mandatory requirement for inclusion in the final proceedings.

Publication

The conference Proceedings will be published and indexed by the Communications in Computer and Information Science (Springer CCIS) and indexed in major digital libraries, including: Scopus, EI-Compendex, DBLP, Google Scholar, Additional Information. Please note that for a paper to be published, at least one of its authors must register for ONLY WEEKEND or ECAI main conference + WEEKEND by early registration deadline.

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Important Dates

  • Submission site opening: 20 March 2025
  • Paper deadline: 20 May 2025
  • Author notification: 7 July 2025
  • Early registration deadline: 20 August 2025
  • Camera ready: 25 July 2025

All deadlines are at the end of the day specified, Anywhere on Earth (AoE) (UTC-12).

Keynote Speaker

Craig Glastonbury

Craig Glastonbury

Human Technopole, Milan, Italy

Biography

Dr Craig A. Glastonbury holds a PhD in computational biology from King’s College London (2013–2017), where he focused on mapping tissue-specific eQTLs across multiple human tissues. He then worked as a Postdoctoral Fellow in Cecilia Lindgren’s lab, applying machine learning to histology.

From 2019 to 2022, Craig was a lead ML researcher at BenevolentAI, focusing on human genetics for target discovery and ML-based patient stratification. His broader research combines histopathology imaging, machine learning, and human genetics. At Human Technopole, his group investigates how genetic variation influences quantifiable phenotypes extracted from diverse biomedical imaging modalities.

He serves on the organizing committee of the International Common Disease Alliance (ICDA), is a guest associate editor for machine learning at AHA Circulation, and an honorary ML researcher at the University of Oxford.

Keynote Title: TBA

Federico Cabitza

Federico Cabitza

University of Milano-Bicocca, Milan, Italy

Biography

Federico Cabitza (BSc, MEng, PhD) is an Associate Professor at the University of Milano-Bicocca, where he leads the Modeling Uncertainty, Decisions, and Interactions Laboratory (MUDILab) and teaches courses in human-computer interaction and decision support.

He has collaborated extensively with hospitals in Milan and co-founded the Medical AI Laboratory. His research focuses on designing and evaluating AI systems for healthcare decision-making and understanding their impact on organizations and workflows.

Author of over 150 publications, Prof. Cabitza has co-chaired international workshops, is listed among Stanford’s Top 2% Scientists, and co-authored the book Artificial Intelligence: The Use of the New Machines with Luciano Floridi.

Keynote Title: Why Accuracy Isn’t Enough: Rethinking Model Evaluation in Clinical AI

Despite widespread use, AI systems in healthcare are often evaluated solely by accuracy. In this talk, Prof. Cabitza questions this approach, proposing a multidimensional framework for model evaluation.

Drawing from recent lab developments, he introduces new metrics and visualization tools that reflect data reliability, case similarity, and clinical utility. He will present a public platform that applies these insights, helping stakeholders understand AI behavior beyond averages—especially in uncertain and diverse clinical scenarios.

Organizing Committee

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Francesco Ciompi

Department of Pathology
Radboud University Medical Center
Nijmegen, The Netherlands

public school email
Sara Moccia

Sara Moccia

Department of Innovative Technologies in Medicine and Dentistry Universitá degli Studi “G. d’Annunzio”
Chieti, Italy

school email
Pietro Liò

Pietro Liò

Department of Computer Science
and Technology, University of Cambridge
Cambridge, United Kingdom

public school email
Antonio Maria Rinaldi

Antonio Maria Rinaldi

Department of Electrical Engineering
and Information Technologies, University of Naples Federico II, Naples, Italy

school email
Cristiano Russo

Cristiano Russo

Department of Electrical Engineering
and Information Technologies, University of Naples Federico II, Naples, Italy

school email
Cristian Tommasino

Cristian Tommasino

Department of Electrical Engineering
and Information Technologies, University of Naples Federico II, Naples, Italy

school email
Mariachiara di Cosmo

Mariachiara Di Cosmo

School of Advanced Studies Sant'Anna Pisa, Italy

school email
Michele Bernardini

Michele Bernardini

Università degli Studi eCampus

school email
Luca Romeo

Luca Romeo

Department of Economics and Law, University of Macerata, Macerata, Italy

school email
Francesco Merolla

Francesco Merolla

Department of Medicine and Health Sciences
"V. Tiberio", University of Molise
Campobasso, Italy

school email

Program Committee

The following experts form the program committee for AIBio 2025:

  • Domenico Amalfitano - University of Naples Federico II, Italy
  • Miriam Angeloni - Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
  • Domenico Benfenati - University of Naples Federico II, Italy
  • Francesco Casadei - IRCCS Institute of Neurological Sciences of Bologna, Italy
  • Michele Ceccarelli - University of Miami, USA / University of Naples Federico II, Italy
  • Angela Crispino - University of Naples Federico II, Italy
  • Giovanni Maria De Filippis - University of Naples Federico II, Italy
  • Aurora Esposito - University of Molise, Italy
  • Luigi Ferraro - University of Naples Federico II, Italy
  • Reet Ghosh - University of Calgary, Canada
  • Marko Harasic - Fraunhofer-Institut FOKUS, Germany
  • Nadieh Khalili - Radboud University Medical Center, Netherlands
  • George Klioumis - Technical University of Crete, Greece
  • Erasmo Purificato - European Commission Joint Research Centre, Italy
  • Francesco Russo - IEOS, Naples, Italy
  • Dario Righelli - University of Naples Federico II, Italy
  • Pierpaolo Vendittelli - Radboud University Medical Center, Netherlands
  • Temitayo Olugbade - University College London, UCL Interaction Centre, London, United Kingdom
  • Jiguang Wang - Hong Kong University of Science and Technology, Hong Kong
  • Maria Chiara Fiorentino - Department of Information Engineering, Polytechnic University of Marche, Italy
  • Massih-Reza Amini - Laboratoire d'Informatique de Grenoble, Université Grenoble Alpes, France
  • Lucia Migliorelli - Department of Information Engineering, Polytechnic University of Marche, Italy
  • Daniele Berardini - Italian Institute of Technology, Genova, Italy
  • Deeptanshu Jha - Alexandria Technology, New York, USA
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Contact

For any request you might have, please contact cristian.tommasino@unina.it.

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