Prof. Dr.-Ing. Kawa Nazemi is organizing together with Prof Dr. Rita Francese and Dr. Laura De Santis  a special issue on “Empowering Patients Through AI, Multimedia, and Explainable HCI: Innovations in Personalized Healthcare” in the Springer Journal for Multimedia Tools and Applications.

This Special Issue explores the transformative role of Artificial Intelligence (AI), Human-Computer Interaction (HCI), and Explainable AI (XAI) in empowering patients within the digital healthcare landscape. While AI-driven technologies such as Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) offer groundbreaking advancements in diagnostics, treatment, and personalized care, their complexity often poses challenges for patient trust and engagement.

Topics of Interest

We invite original research, reviews, and case studies that focus on patient empowerment through AI, multimedia, XAI, and HCI. Topics include, but are not limited to:

1. Explainable HCI for Multimedia-Enhanced Patient Tools

Patients are empowered when they can access and interpret their health data easily. HCI and XAI can enhance multimedia applications that present real-time, personalized, and actionable health information.

• Transparent Wearable Interfaces: Devices that clearly explain health metrics through intuitive, XAI-driven feedback.
• Interactive Health Apps: Multimedia platforms providing explainable and personalized recommendations for managing patient health.
• AI-Powered Virtual Health Coaches: Conversational agents offering clear, actionable advice for disease prevention and management.

2. Explainable Diagnostics and Patient-Centered Interfaces

AI diagnostics must empower patients by making complex information digestible and actionable. Tools designed with XAI and HCI principles can help patients make sense of medical insights.

• Patient-Facing Diagnostic Tools: Multimedia systems with explainable imaging/video insights that clarify diagnoses.
• HCI-Driven Medical Visualizations: Interactive tools to simplify lab results, imaging reports, and AI predictions.
• Multimodal Patient Interfaces: Combining visuals, text, and interactivity to explain complex medical concepts intuitively.

3. HCI and XAI in Mental Health Management

Mental health tools must empower patients to recognize and manage their well-being. Transparent and explainable AI systems can improve accessibility and trust.

• Mental Health Apps: Multimodal platforms with explainable insights into emotional and behavioral data.
• Transparent Behavior Analysis: XAI systems for early detection of mental health risks through video and audio analysis.
• Accessible Neurofeedback Tools: Patient-friendly cognitive tools that explain therapeutic results in simple terms.

4. Trustworthy and Ethical XAI for Healthcare Multimedia

Empowerment requires trust. Human-centered design and ethical frameworks ensure multimedia AI tools are transparent, fair, and inclusive.

• Trust-Building Design: Transparent AI systems that prioritize accountability, fairness, and clarity.
• Bias Mitigation: Inclusive multimedia tools that avoid biases and serve diverse patient populations.
• Explainability and Privacy: XAI frameworks that ensure patient data privacy while delivering meaningful insights.

5. Patient Education and Engagement Through XAI

Educational tools empower patients by improving health literacy and fostering engagement. XAI-driven multimedia platforms make complex health information clear, interactive, and engaging.

• Explainable Health Literacy Tools: Multimedia platforms using intuitive explanations to educate patients.
• Gamification for Health Behaviors: Interactive, multimedia games that guide patients in adhering to treatments and lifestyle changes.
• Tracking Patient-Reported Outcomes: Visual tools that explain patient health metrics in clear and accessible formats.

6. Technical and Multimedia Innovations for Healthcare

Technical innovations in multimedia AI systems can empower patients by offering engaging, explainable, and actionable healthcare solutions.

• Interactive Medical Tools: Systems for analyzing videos/images with intuitive XAI-driven insights.
• Multimodal Data Fusion: Combining wearable, sensor, and imaging data to provide explainable and engaging outputs.
• AR/VR for Patient Education: XAI-powered augmented reality tools for interactive health learning and surgical planning.

7. Ethical and Regulatory Considerations

Ensuring ethical transparency and regulatory compliance is critical for developing multimedia tools that empower patients without compromising privacy or fairness.

• Ethical Frameworks: Guidelines for fairness, transparency, and accountability in XAI-driven multimedia tools.
• Regulatory Compliance: Multimedia systems that meet global standards while empowering patients.
• Privacy-Aware XAI: Balancing data privacy with clear, meaningful, and actionable patient insights.

8. Enhancing Physician Support Through Integrated AI and Multimedia Solutions
   Empowering physicians is essential to improving patient care. By leveraging explainable AI (XAI), visualizations, or advanced human-computer interaction (HCI), healthcare providers can access intuitive and actionable insights that enhance their diagnostic and decision-making processes while fostering better patient collaboration.

• Explainable Decision Support Systems leveraging AI and visual interfaces to aid physicians in making informed decisions for patients
• Multimedia and Visual Analytics for Clinical Use: Interactive dashboards combining patient data, imaging, and wearable metrics to streamline and clarify complex medical information.
• Collaborative Physician-Patient Interfaces: Tools designed to bridge communication gaps by integrating explainable patient insights with medical workflows, ensuring shared understanding and collaborative care.

If you are interested in the journal and in submitting an article, please note the information on the special issue website: Special Issue “Empowering Patients Through AI, Multimedia, and Explainable HCI: Innovations in Personalized Healthcare“.