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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:20260119T114825Z
CREATED:20250228T152706Z
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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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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240830
DTEND;VALUE=DATE:20250116
DTSTAMP:20240626T152648Z
CREATED:20231103T204642Z
LAST-MODIFIED:20240626T152648Z
UID:12408-1724976000-1736985599@vis.h-da.de
SUMMARY:Call for Papers: Electronics - Special Issue - "Unlocking Data’s Potential: Artificial Intelligence and Visual Analytics in the Modern Age"
DESCRIPTION:In the rapidly evolving fields of artificial intelligence (AI) and visual analytics\, there is growing recognition of their combined potential to reshape diverse sectors\, emerging as a crucial pathway for progressing research and practical applications. The synergy between AI-driven techniques—such as natural language processing\, image and video processing\, and data analytics—and visual analytics methodologies augments our ability to decipher complex data structures. Such interdisciplinary approaches reveal subtle data patterns\, enhancing decision-making processes and establishing more effective predictive mechanisms essential for addressing societal and economic challenges and progress. \nThis Special Issue endeavors to delve deep into the interplay between AI and visual analytics\, seeking contributions highlighting novel methodologies\, computational strategies\, systematic reviews\, and system architectures of real-world applications. Our goal is to foster an interdisciplinary exchange of ideas\, extending to areas including analytical decision-making\, corporate strategy evolution\, AI-driven collaborative frameworks\, healthcare analytics\, sustainability metrics\, and innovative techniques for behavior and trend detection. \nIn the current era\, where data stand as the backbone of contemporary challenges and opportunities\, this Special Issue serves as a platform for researchers and professionals to showcase pioneering work\, laying the foundation for breakthroughs that cater to the multifaceted challenges of our society. By combining AI and visual analytics\, we are able to unlock unprecedented insights from data\, driving our global community toward a more resilient and prosperous future. \nTopics of interest include\, but are not limited to\, the following: \n\nIntegrative visual analytics and artificial intelligence systems and approaches;\nAI and visual analytics to support decision-making;\nTechniques and methods in explainable AI;\nVisual analytic solutions for handling big data challenges;\nAI and visual analytics in strategic corporate planning;\nAI and visual analytics in healthcare;\nAI and visual analytics for social well-being and mental health;\nFacilitation of collaborative work through AI interventions;\nInsights into collaborative intelligence mechanisms;\nAI and visual analytics for sustainability and environmental analysis and management;\nAI and visual analytics for policy modeling and political decision support.\n\nProf. Dr. Kawa Nazemi\nProf. Dr. Nuno Datia\nProf. Dr. Rita Francese\nGuest Editors \n  \nManuscript Submission Information \n  \nManuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered\, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles\, review articles as well as short communications are invited. For planned papers\, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. \nSubmitted manuscripts should not have been published previously\, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI. \nPlease visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI’s English editing service prior to publication or during author revisions. \n  \n\nKeywords\n\n\nartificial intelligence (AI)\nvisual analytics\nnatural language processing\nexplainable AI\nbig data analytics\ndata interpretation
URL:https://vis.h-da.de/events/call-for-papers-artificial-intelligence-and-visual-analytics-in-the-modern-age
CATEGORIES:Journal,Research
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