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X-WR-CALNAME:Human-Computer Interaction & Visual Analytics Reasearch Department (vis) at Darmstadt University of Applied Sciences (h_da)
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X-WR-CALDESC:Events for Human-Computer Interaction & Visual Analytics Reasearch Department (vis) at Darmstadt University of Applied Sciences (h_da)
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DTSTART;VALUE=DATE:20260731
DTEND;VALUE=DATE:20260801
DTSTAMP:20260404T042347
CREATED:20250228T152706Z
LAST-MODIFIED:20260119T114825Z
UID:13312-1785456000-1785542399@vis.h-da.de
SUMMARY:Call for Papers: Multimedia Tools and Applications
DESCRIPTION:The empowerment of patients is emerging as a central focus in the digital transformation of healthcare. The integration of Artificial Intelligence (AI)\, Human-Computer Interaction (HCI)\, and Explainable AI (XAI) presents an unprecedented opportunity to develop transparent\, intuitive\, and patient-centered technologies. However\, while AI advancements—such as Machine Learning (ML)\, Deep Learning (DL)\, and Natural Language Processing (NLP)—offer transformative tools for diagnostics\, treatment\, and personalized care\, their complexity often limits patients’ trust\, understanding\, and engagement. \nPatient empowerment relies on solutions that demystify complex AI-driven insights\, fostering trust and enabling individuals to actively participate in their healthcare journey. Explainable AI (XAI) addresses this need by making AI outputs interpretable and transparent\, ensuring patients can comprehend and trust the information being presented. Combined with HCI principles\, XAI-enabled multimedia tools—such as medical videos\, images\, interactive dashboards\, wearable devices\, and virtual health assistants—make health data more engaging\, accessible\, and actionable. \nThis Special Issue explores how the convergence of AI\, HCI\, and multimedia technologies can empower patients through tools that improve health literacy\, facilitate informed decision-making\, and foster collaboration with clinicians. By prioritizing patient trust\, transparency\, and accessibility\, these innovations aim to transform healthcare into a truly inclusive and empowering experience. \nGoals of the Special Issue \n\nHighlight innovative multimedia tools that prioritize patient empowerment through AI\, HCI\, and XAI.\nExplore how explainable systems improve patient understanding\, trust\, and engagement with healthcare AI solutions.\nAddress the design challenges of creating inclusive\, ethical\, and patient-centered multimedia applications.\nFoster collaboration among researchers\, multimedia experts\, clinicians\, patients\, and caregivers to build empowering healthcare solutions.\n\nTopics of Interest \nWe 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: \nExplainable HCI for Multimedia-Enhanced Patient Tools \nPatients 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. \n\nTransparent Wearable Interfaces: Devices that clearly explain health metrics through intuitive\, XAI-driven feedback.\nInteractive Health Apps: Multimedia platforms providing explainable and personalized recommendations for managing patient health.\nAI-Powered Virtual Health Coaches: Conversational agents offering clear\, actionable advice for disease prevention and management.\n\nExplainable Diagnostics and Patient-Centered Interfaces \nAI 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. \n\nPatient-Facing Diagnostic Tools: Multimedia systems with explainable imaging/video insights that clarify diagnoses.\nHCI-Driven Medical Visualizations: Interactive tools to simplify lab results\, imaging reports\, and AI predictions.\nMultimodal Patient Interfaces: Combining visuals\, text\, and interactivity to explain complex medical concepts intuitively.\n\nHCI and XAI in Mental Health Management \nMental health tools must empower patients to recognize and manage their well-being. Transparent and explainable AI systems can improve accessibility and trust. \n\nMental Health Apps: Multimodal platforms with explainable insights into emotional and behavioral data.\nTransparent Behavior Analysis: XAI systems for early detection of mental health risks through video and audio analysis.\nAccessible Neurofeedback Tools: Patient-friendly cognitive tools that explain therapeutic results in simple terms.\n\nTrustworthy and Ethical XAI for Healthcare Multimedia \nEmpowerment requires trust. Human-centered design and ethical frameworks ensure multimedia AI tools are transparent\, fair\, and inclusive. \n\nTrust-Building Design: Transparent AI systems that prioritize accountability\, fairness\, and clarity.\nBias Mitigation: Inclusive multimedia tools that avoid biases and serve diverse patient populations.\nExplainability and Privacy: XAI frameworks that ensure patient data privacy while delivering meaningful insights.\n\nPatient Education and Engagement Through XAI \nEducational tools empower patients by improving health literacy and fostering engagement. XAI-driven multimedia platforms make complex health information clear\, interactive\, and engaging. \n\nExplainable Health Literacy Tools: Multimedia platforms using intuitive explanations to educate patients.\nGamification for Health Behaviors: Interactive\, multimedia games that guide patients in adhering to treatments and lifestyle changes.\nTracking Patient-Reported Outcomes: Visual tools that explain patient health metrics in clear and accessible formats.\n\n Technical and Multimedia Innovations for Healthcare \nTechnical innovations in multimedia AI systems can empower patients by offering engaging\, explainable\, and actionable healthcare solutions. \n\nInteractive Medical Tools: Systems for analyzing videos/images with intuitive XAI-driven insights.\nMultimodal Data Fusion: Combining wearable\, sensor\, and imaging data to provide explainable and engaging outputs.\nAR/VR for Patient Education: XAI-powered augmented reality tools for interactive health learning and surgical planning.\n\n Ethical and Regulatory Considerations \nEnsuring ethical transparency and regulatory compliance is critical for developing multimedia tools that empower patients without compromising privacy or fairness. \n\nEthical Frameworks: Guidelines for fairness\, transparency\, and accountability in XAI-driven multimedia tools.\nRegulatory Compliance: Multimedia systems that meet global standards while empowering patients.\nPrivacy-Aware XAI: Balancing data privacy with clear\, meaningful\, and actionable patient insights.\n\nEnhancing Physician Support Through Integrated AI and Multimedia Solutions\n \nEmpowering 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. \n\nExplainable Decision Support Systems leveraging AI and visual interfaces to aid physicians in making informed decisions for patients\nMultimedia and Visual Analytics for Clinical Use: Interactive dashboards combining patient data\, imaging\, and wearable metrics to streamline and clarify complex medical information.\nCollaborative Physician-Patient Interfaces: Tools designed to bridge communication gaps by integrating explainable patient insights with medical workflows\, ensuring shared understanding and collaborative care.\n\n  \nConclusion \nThis Special Issue aims to showcase how Explainable AI\, Human-Computer Interaction\, and multimedia innovations can converge to empower patients. By focusing on trust\, accessibility\, and clarity\, these tools can transform patients from passive recipients into active participants in their healthcare journey. \nWe invite contributions that advance patient-centered solutions\, ensuring that healthcare technologies are not only innovative but also empowering\, inclusive\, and impactful. \n 
URL:https://vis.h-da.de/events/call-for-papers-empowering-patients-through-ai-multimedia-and-explainable-hci-innovations-in-personalized-healthcare
CATEGORIES:Journal,Research
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DTSTART;VALUE=DATE:20260330
DTEND;VALUE=DATE:20260801
DTSTAMP:20260404T042347
CREATED:20260226T134513Z
LAST-MODIFIED:20260226T135624Z
UID:13607-1774828800-1785542399@vis.h-da.de
SUMMARY:Call for Papers - International Conference Information Visualisation (IV2026) - Submission Deadline 30. March 2026
DESCRIPTION:IV2026 – 30th International Conference Information Visualisation & AI2026 – 7th International Conference AI & Visualisation \n28 – 31 July 2026 \nSOAS University of London London\, United Kingdom \nhttps://iv.csites.fct.unl.pt/uk/ \n  \nCall for Papers\, Poster\, and Participation \n  \nTheme and scope are planned as a series of symposia with details\, and further information is available at IV2026: https://iv.csites.fct.unl.pt/uk/symposia/ \nSubmission Portal: https://www.conftool.org/IV-cgiv-2026/ \nImportant Dates – https://iv.csites.fct.unl.pt/uk/call-for-papers/important-dates/ \n  \n\nIV2026 Thematic symposia\n\nInfVis  – Information Visualisation Theory & Practice\nIV-App – Applications of Information Visualization\nGlyphs – Data Glyphs – Shapes\, Icons\, and other Graphic Elements in Visualization\nIVE – Information Visualization Evaluation\nHCI – Human-Computer Interaction for Information Visualization\nGTNV – Graph Theory & Network Visualization – GTNV-Poster\n\nKnowledge Visualisation \n\nKV – Knowledge Visualization and Visual Thinking\n(Gen)AI-TEL – 1st (Generative) AI in Technology-Enhanced Learning\nMuVis – Music Visualization\nDHKV – Digital Humanities Knowledge Visualisation\n\nAI-Viz26 – 7th International Conference AI&Visualisation\n\nAI-VIZ – AI&Visualisation\nVA – 14 International Symposium Visual Analytics and Artificial Intelligence\nAI&VKD – 7th AI and Visual Knowledge Discovery\nEIaiV – Explainable and Interpretable AI through Visualisation\nAI_GT – AI\, Games & Theatre Symposium\n\nvis2026 \n\nAI-EVC – 4th  Symposium on AI Empowered Visual Computing\nARVA – Augmented Reality Visualization and Art\nD-ART – Symposium of Digital Art and Gallery\nVIS – Visualization\nVAD – Visualization\, Art\, & Design\nCAivDE – Computer Animation\, Information Visualisation\, and Digital Effects\nDE – Digital Entertainment\nCGa – Computer Games and their applications\n\nMediVis2026 \n\nAIMH – 5th Visualization and Artificial Intelligence for Medicine\, Healthcare and Social Good\n\nBuiltViz2026 \n\nSE_AIV – Sustainability and Environmental AI-Visualization\nVAI_BuiltViz-International Conference Visualisation and AI for Heritage\, Architecture\, and Sustainable Urban and Rural Environments\n\n\nGMAI2026 \n\nGMAI – Geometric Modelling and Imaging\n\n \n  \nPreconference course:     Doctoral Research Workshop \nResearcher Link Forum:   Research Project Collaboration \nFocus Group Publication: Post-conference publication \n  \nGeneral Co-Chairs:\nEbad Banissi (Em Prof.)\, LSBU\, UK \n\nSymposium General Co-Chairs:\nKawa Nazemi (Prof. Dr.)\, Darmstadt University of Applied Sciences\, DE – European University of Technolgy (EUt+) – hessian.AI\nBoris Kovalerchuk (Prof.)\, University of Central Washington\, USA – AI and Visual Knowledge Discovery\nUrska Cvek (Prof.)\, Louisiana State University\, USA – Visualization and Artificial Intelligence for Medicine\, Healthcare \nAnna Ursyn (Prof.)\, University of Northern Colorado\, USA – Digital Art and Gallery
URL:https://vis.h-da.de/events/international-conference-information-visualisation-iv2026-2
LOCATION:SOAS University London\, 10 Thornhaugh St\, London WC1H 0XG\, United Kingdom
CATEGORIES:Conference,Event,Research
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