The empowerment of patients is emerging as a central focus in the digital transformation of healthcare. By integrating Artificial Intelligence (AI), Human-Computer Interaction (HCI), and Explainable AI (XAI), we aim to develop transparent, intuitive, and patient-centered technologies focusing on multimedia applications.

Explainable AI (XAI) enhances trust and engagement by making AI outputs interpretable and transparent. Coupled with HCI principles, multimedia tools—such as interactive dashboards, wearable devices, and virtual health assistants—can empower patients to actively participate in their healthcare journey. This workshop explores how these technologies improve health literacy, facilitate informed decision-making, and foster collaboration with clinicians.  

Special Issue

Selected papers will be invited to submit an extension to the Special Issue "Empowering Patients Through AI, Multimedia, and Explainable HCI: Innovations in Personalized Healthcare [1261]" -  Multimedia Tools and Applications.

Topics

• Explainable HCI for Multimedia-Enhanced Patient Tools

Transparent Wearable Interfaces: Devices that explain health metrics through XAI-driven feedback.

Interactive Health Apps: Multimedia platforms offering explainable and personalized recommendations.

AI-Powered Virtual Health Coaches: Conversational agents providing clear, actionable advice.

• Explainable Diagnostics and Patient-Centered Interfaces

Patient-Facing Diagnostic Tools: Multimedia systems that clarify diagnoses with explainable imaging insights.

HCI-Driven Medical Visualizations: Interactive tools simplifying lab results and AI predictions.

Multimodal Patient Interfaces: Combining visuals, text, and interactivity to explain complex medical concepts.

• HCI and XAI in Mental Health Management

Mental Health Apps: Platforms providing explainable insights into emotional and behavioral data.

Transparent Behavior Analysis: XAI systems for early detection of mental health risks.

Accessible Neurofeedback Tools: Patient-friendly cognitive tools for therapeutic explanations.

• Trustworthy and Ethical XAI for Healthcare Multimedia

Trust-Building Design: Transparent AI systems ensuring accountability and fairness.

Bias Mitigation: Inclusive multimedia tools serving diverse populations.

Explainability and Privacy: Balancing patient data privacy with clear insights.

• Patient Education and Engagement Through XAI

Explainable Health Literacy Tools: Platforms using multimedia to educate patients intuitively.

Gamification for Health Behaviors: Interactive games guiding treatment adherence and lifestyle changes.

Tracking Patient-Reported Outcomes: Visual tools for clear explanations of health metrics.

• Technical and Multimedia Innovations for Healthcare

Interactive Medical Tools: Systems analyzing videos/images with explainable insights.

Multimodal Data Fusion: Integrating wearable and sensor data for actionable healthcare solutions.

AR/VR for Patient Education: XAI-powered augmented reality for interactive health learning.

• Ethical and Regulatory Considerations

Ethical Frameworks: Guidelines for fairness, transparency, and accountability.

Regulatory Compliance: Systems meeting global standards while empowering patients.

Privacy-Aware XAI: Ensuring privacy without compromising meaningful insights.

Enhancing Physician Support Through Integrated AI and Multimedia Solutions

Explainable Decision Support Systems: Tools aiding physicians in informed decision-making.

Multimedia and Visual Analytics for Clinical Use: Dashboards combining imaging and patient data.

Collaborative Physician-Patient Interfaces: Bridging communication gaps through explainable insights.

Target Audience 

The EMPATH-IA workshop is designed for an interdisciplinary audience, including:

• Researchers and Academics: Experts in Human-Computer Interaction (HCI), Artificial Intelligence (AI), Machine Learning (ML), Explainable AI (XAI), and multimedia applications in healthcare.

• Healthcare Professionals: Physicians, clinicians, psychologists, and medical researchers interested in AI-driven decision support tools.

• Technology Developers: Engineers, software developers, and UX/UI designers working on wearable technology and multimedia healthcare interfaces.

• Regulatory and Ethical Experts: Policymakers and professionals focusing on ethical, legal, and regulatory aspects of AI in healthcare.

• Industry Representatives: Companies developing AI-based healthcare solutions, including startups and medical device manufacturers.

• Graduate Students and Early-Career Researchers: Those interested in exploring AI, multimedia, and explainable HCI applications in healthcare.

Submission Type

• • Full Papers: Minimum of 10 standard pages (one standard page corresponds to 2,500 characters), plus an appropriate number of references.

  • Short Papers: Between 4 and 6 standard pages, including references