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Workshop on Data-Driven Models for Digital Health Transformation - DMDH 2025

10 - 12 June, 2025 - Bilbao, Spain

In conjunction with the 14th International Conference on Data Science, Technology and Applications - DATA 2025


CO-CHAIRS

Lerina Aversano
Department of Agricultural Science, Universita di Foggia
Italy
 
Brief Bio
Lerina Aversano is a full professor at the Dept. of Agricultural Science, Food, Natural Resources and Engineering at the University of Foggia, Italy. She received the Ph.D. in Computer Engineering in July 2003 at the University of Sannio where she has been assistant professor from 2005. She also was a research leader at RCOST – Research Centre On Software Technology – of the University of Sannio from 2005. Her current research interests lie at the intersection of software engineering and data analytics and aim to advance research and practice more specifically in different application domains. In these fields she has published numerous articles in international journals, books and conference proceedings.
Martina Iammarino
Department of Computer Science and Technologies, Pegaso University
Italy
 
Brief Bio
MARTINA IAMMARINO obtained her master's degree and Ph.D. in Information Technology for Engineering from the University of Sannio, Benevento, Italy, in 2019 and 2023, respectively. She is currently a Researcher at the Department of Information Science and Technology at Pegaso University, Naples, Italy. Her research focuses on software engineering, with particular attention to software and data quality, as well as process and data engineering. In recent years, she has explored the application of artificial intelligence techniques, particularly machine learning and deep learning, in various domains, with a specific focus on the medical field. Her studies have been dedicated to validating artificial intelligence models to support diagnosis and improve healthcare processes, with a strong emphasis on transparency and explainability of the models used in clinical settings. She has authored numerous publications in international journals and conferences, contributing to the development of advanced methodologies for software quality management and data-driven process optimization. Additionally, she has served as a reviewer for prestigious international journals and conferences and has been a member of program and organizing committees for significant scientific events. She is one of the main organizers of the CISE special session, Computational Intelligence in Software Engineering, held within IJCNN 2024, and the special session Artificial Intelligence in Software Quality and Evolution, which will take place at IJCNN 2025. In parallel, she is committed to promoting interdisciplinary research, collaborating with experts from various fields to foster the integration of artificial intelligence into critical systems, with particular attention to healthcare applications.
Antonella Madau
Department of Engineering, University of Sannio
Italy
 
Brief Bio
ANTONELLA MADAU received the master’s degree in computer engineering, in 2022, and the Ph.D. degree from the University of Sannio, Benevento, Italy. She has authored or coauthored some papers in international conferences related to her research areas, which include the application of artificial intelligence techniques, such as machine learning and deep learning in the domains of public administration and digital health. Her research field is also involved in the use of open data and analytics. She was a reviewer for international conferences.

SCOPE

The workshop explores how data can enable the development of explainable models in digital health, addressing the need for transparency and trust in AI-driven solutions. It focuses on integrating advanced data science techniques into healthcare applications, including clinical decision support, medical imaging, and diagnostics. Key themes include frameworks for explainability, ethical and privacy considerations, and the role of data engineering in creating robust digital health systems. Participants will discuss emerging trends, challenges, and best practices, fostering collaboration between academia, industry, and healthcare providers. The workshop aims to promote the adoption of explainable AI solutions that improve patient outcomes, optimize healthcare processes, and ensure compliance with ethical and regulatory standards in digital health.

TOPICS OF INTEREST

Topics of interest include, but are not limited to:
  • Data science techniques for explainable healthcare models
  • Machine learning and data visualization in clinical applications
  • Ethical and privacy considerations for healthcare data
  • Integration of data-driven models in digital health workflows
  • Case studies: Explainable AI in medical imaging and diagnostics
  • Emerging trends in data engineering for digital health

IMPORTANT DATES

Paper Submission: April 7, 2025
Authors Notification: April 22, 2025
Camera Ready and Registration: May 2, 2025

WORKSHOP PROGRAM COMMITTEE

Available soon.

PAPER SUBMISSION

Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines.
Papers must be submitted electronically via the web-based submission system using the appropriated button on this page.

PUBLICATIONS

After thorough reviewing by the workshop program committee, all accepted papers will be published in the workshop proceedings book, under an ISBN reference and on digital support.
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/).
SCITEPRESS is a member of CrossRef (http://www.crossref.org/) and every paper is given a DOI (Digital Object Identifier).

SECRETARIAT CONTACTS

DATA Workshops - DMDH 2025
e-mail: data.secretariat@insticc.org
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