*** Apologies for cross-posting *** ------------------------------------------------------ CALL FOR PAPERS: Responsible AI in Healthcare Collection Discover Artificial Intelligence ------------------------------------------------------ We are delighted to invite submissions to a new topical collection on **"Responsible AI in Healthcare: Bridging Technical Innovation and Multi-Stakeholder Needs"** in Discover Artificial Intelligence. As AI becomes increasingly embedded in clinical decisions, patient care pathways, and health outcomes, the need for systems that are not only technically robust but also trustworthy, equitable, and aligned with diverse stakeholder needs becomes critical. This collection emphasizes **operationalizing responsible AI** across the healthcare ecosystem—going beyond explainability to address governance, ethics, workflow integration, fairness, bias mitigation, privacy, accountability, and inclusive design. == Important Dates == * Submission Deadline: October 5, 2026 == Submission Guidelines == * Article Types: Research, Review, Brief Report, Case Study, Methodology, Perspective, and others * Format: Follow Discover Artificial Intelligence submission guidelines * Submission Portal: https://www.springer.com/journal/44163/submission-guidelines * Note: In the submission system, select this collection from the drop-down menu on the 'Details' tab == Collection Focus == We particularly welcome research demonstrating how AI systems can be **designed, validated, and implemented collaboratively** with clinicians, patients, researchers, administrators, and policymakers to ensure inclusive, equitable, trustworthy, and effective outcomes in real-world healthcare settings. We invite contributions that combine technical rigor with practical impact, spanning machine learning, multimodal health data, wearable and sensor-based systems, human-computer interaction, and ethical design in domains such as digital health, neurorehabilitation, clinical decision support, and telehealth. == Topics of Interest == Building on emerging trends and challenges in responsible healthcare AI, we welcome submissions that address, but are not limited to: 1. **Human-Centered AI and Participatory Design** - Co-design methodologies in healthcare AI - Stakeholder engagement strategies - Multi-stakeholder collaboration frameworks 2. **Fairness and Bias Mitigation** - Algorithmic fairness in clinical contexts - Equitable AI deployment - Bias detection and mitigation strategies 3. **Clinical Integration and Validation** - Workflow integration of AI tools - Clinical validation methodologies - Evaluation frameworks for healthcare AI 4. **Governance and Implementation** - Regulatory and ethical frameworks - Responsible data governance - Privacy preservation and informed consent - Implementation case studies 5. **Domain-Specific Applications** - AI-driven neurorehabilitation tools - Wearable systems and adaptive interfaces - Clinical decision support systems - Telehealth and remote care AI 6. **AI Communication and Interaction** - Natural language processing for health communication - Conversational AI for ethical decision support - Explainable AI in clinical contexts 7. **Data and Modeling** - Multimodal data fusion - Personalized healthcare using AI - Digital biomarkers and predictive modeling == About the Journal == Discover Artificial Intelligence is a transdisciplinary open access journal publishing research on all aspects of AI theory, methodology, and applications (SJR 2024: 0.876, Q1). The journal offers a median time to first decision of 23 days. **Open Access Funding:** Many institutions have existing agreements with Springer Nature. Check your institution's funding eligibility at: https://www.springernature.com/gp/open-science/funding/articles#c14214262 == Guest Editors == * Giuseppe Prencipe, Associate Professor, University of Pisa, Italy * Silvia Filogna, Researcher, IRCCS Fondazione Stella Maris, Italy * Tommaso Turchi, Assistant Professor, University of Pisa, Italy This collection provides a platform for interdisciplinary contributions spanning computer science, biomedical engineering, clinical research, ethics, and policy, supporting **SDG 9: Industry, Innovation and Infrastructure**. **Full collection details:** https://link.springer.com/collections/ccieiafgad For questions or more information, please contact Tommaso Turchi at tommaso.turchi(a)unipi.it We look forward to your contributions! #ResponsibleAI #HealthcareAI #HumanCenteredAI #ExplainableAI #AlgorithmicFairness #ClinicalAI