SilverTech

Introduction

The effective analysis and integration of healthcare data are crucial in modern healthcare. Data come in diverse formats (e.g., images, signals, and wavelengths etc.) from multiple stakeholders but often but lack integration and valuable information. Electronic Health Records (EHRs) facilitate data sharing across institutions, enabling improved quality assurance, disease surveillance, and research. Additionally, wearable devices and the Internet of Things (IoT) contribute to the expansion of healthcare data, but their integration with historical medical data still remains a challenge.

Currently, AI-driven healthcare models primarily utilize patient data, often  lifestyle, behavioral, and genomic information, which are essential for personalized, patient-centric care. The lack of integrated data sources, such as Patient-Reported Outcome Measures (PROMs) and Patient-Reported Experience Measures (PREMs), limits precision medicine and personalized interventions. Furthermore, many treatment protocols focus on life extension while overlooking patients’ Quality of Life (QoL) and well-being.

Timely diagnosis and multimodal data analysis are vital for early detection, precision treatment, and effective prevention strategies. However, fragmented healthcare data hinder the understanding of causal risk factors, and current approaches often follow a one-size-fits-all model. Personalization should account for comorbidities, genetic predisposition, and environmental factors.

Advanced technologies—such as Artificial Intelligence (AI), Big Data, and Ambient Assisted Living (AAL)—offer potential solutions for improved risk prediction, prevention, and intervention. Innovations in AI, wearable devices, robotics, and telemedicine have enhanced healthcare delivery, especially for aging populations. Integrating these technologies with human-centered approaches and the European Health Data Space (EHDS) initiative will enable personalized recommendations, behavioral changes, and long-term improvements in patient care.

Aim of the Workshop

This Workshop aims to showcase cutting-edge advancements in healthcare technologies and explore how these innovations can shape the future of healthcare for ageing populations. Key focus areas include developing intelligent systems for early detection and risk stratification, creating assistive technologies for improved QoL, and leveraging integrated big data and interoperable platforms to ensure seamless healthcare delivery across diverse settings. The Workshop also seeks to highlight challenges such as ethical considerations, usability, scalability, and data privacy, while emphasizing interdisciplinary collaboration and the socio-technical integration of solutions.

Topics

In this context, the aim of this Workshop is to present research results on technologies, tools and methods that support the development, deployment, and operation of advanced AI and Big Data systems. It will feature a mix of research paper presentations, and live demonstrations, encouraging interaction among researchers, practitioners, and industry experts. The main topics of interest include, but are not limited to:

• Intelligent AI-enabled systems for early detection and risk stratification of age-related conditions
• Personalization of healthcare services using AI and machine learning
• Assistive robotics for mobility, rehabilitation, and independent living
• Wearable technologies and remote monitoring solutions
• Advanced sensors for non-invasive health diagnostics
• Interoperable platforms for integrated healthcare delivery
• Predictive analytics for patient outcome optimization
• Human-centric design in healthcare technologies
• Ethical frameworks for the deployment of AI in healthcare
• Data fusion and semantic interoperability in health systems
• Telemedicine and digital health interventions
• Multi-modal interaction systems for patient engagement
• Cybersecurity and privacy in health data management
• Real-time edge computing applications in healthcare
• Gamification and VR/AR for patient rehabilitation and training
• Caregiver support tools and collaboration platforms
• Serious Games and Gamification (SGG) approaches towards personalization of prevention and intervention measures
• Future research challenges in mHealth

For Authors

This workshop will only accept for review original papers that have not been previously published. Papers must be prepared in English and the length of them should be up to 14 PAGES (with references included), formatted according to the well known Springer Lecture Notes in Computer Science (LNCS) series format. Please note that the minimum length of submitted papers must be no less than 8 pages. Manuscripts with less than 8 pages long will not be taken into consideration for the Conference and they will immediately be rejected.

Authors are strongly advised to submit their manuscripts both through the official conference submission form and via a direct email to gmanias@unipi.gr and dimos@unipi.gr. This will ensure that their papers are reviewed and published as part of the Workshop.

Accepted papers will be published in the AIAI2025 conference proceedings in the Springer IFIP AICT Series Proceedings and they will be available on line. (https://ifipaiai.org/2025/call-for-papers/) and will also be presented directly in the Workshop. All papers will be reviewed and evaluated by independent experts and selected based on their originality, merit, and relevance to the workshop.

Fees: Following the guidelines of the conference (https://ifipaiai.org/2025/registration/)

Important Dates

(these dates apply only for this workshop. Authors must pay attention to the camera ready date ):

• Paper Submission Deadline: March 20, 2025
• Notification of Acceptance/Rejection: April 2, 2025
• Camera Ready Submission/Registration: April 13, 2025
• Early / Author registration by: 13th of April, 2025
  
• Conference Dates: 26-29 of June, 2025
  

Dates of the Workshop

The Workshop will be held in the context of the AIAI2025 conference (https://ifipaiai.org/2025/) during 26^th-29^th of June in Limassol, Cyprus.

Workshop Format and agenda

The Workshop, will be conducted under the auspices of the COMFORTage EU Funded project, and will be initiated by a demo application and presentation, entitled “Clinical DSS and AI models for personalized recommendations and early prevention measures to raise awareness of relevant factors of dementia and frailty”. The latter seeks to highlight requirements and needs towards personalized eHealth solutions for predicting and relieving from dementia and frailty. Two introduction talks will be provided by invited speakers, being followed by accepted paper presentations.  

Invited speakers

We have confirmed the participation of the following invited speakers with expertise within the field of AI-based personalized healthcare applications both from technical and medical perspectives:

• Dr. Athos Antoniades, STREMBLE Ventures LTD
• Prof. Spyros Likothanasis, Computer Engineering and Informatics Department, University of Patras

Workshop chairs

Dr. George Manias: Department of Digital Systems, University of Piraeus
Dr. Efthyvoulos Kyriacou: Department of Electrical, Computer Engineering and Informatics, Cyprus University of Technology
Prof. Dimosthenis Kyriazis: Department of Digital Systems, University of Piraeus
Prof. Spyridon Likothanassis: Computer Engineering and Informatics Department, University of Patras
Prof. Andreas Andreou: Department of Electrical, Computer Engineering and Informatics, Cyprus University of Technology