Call for Papers

• Original research contributions submitted for publication in the indexed conference proceedings.

• Work-in-progress, preliminary results, and concise research contributions. 

• Interactive sessions (90 minutes) focused on emerging topics.

• Expert discussions on focused topics, including audience interaction.

• Pre-conference sessions (3 hours) providing in-depth training.

• Practical presentations of systems, tools, or applications.

This track addresses the protection and continuity of digital health services under crisis, conflict, and cyberattack, from military and disaster medicine to the integrity of health information itself.

• Health data in military medicine, defence, and crisis response

• Cybersecurity and risk management in health systems

• Continuity planning and resilience of digital health services

• Secure data collection and analytics in emergency settings

• Ethical and legal challenges of dual-use health data

• Health misinformation, disinformation, and infodemic management

This track covers the empirical evaluation of digital health in real settings, including clinical, economic, environmental, and implementation outcomes, and the methods for scaling interventions beyond their first site.

• Real-world evidence and pragmatic trials

• Clinical trials of digital health technologies, including decentralised and adaptive designs

• Cost-benefit and cost-effectiveness analysis

• Implementation science and adoption research

• Methodological innovations in digital health evaluation

• Post-market surveillance of AI-enabled health technologies

• Reproducibility, transparency, and open science in evaluation pipelines

• Environmental impact assessment of digital health technologies and services

• Scale-up, spread, and sustainability of digital health interventions across settings and health systems

This track covers the infrastructure of health data: the European Health Data Space, standards and semantic interoperability, information systems, and the quality, governance, and sustainability of the data pipelines they run on. It spans primary and secondary use across borders and organisations.

• EHDS readiness and secondary use

• Federated, privacy-preserving learning

• FAIR data, standards, terminologies, and semantic interoperability

• Cross-border data collaborations

• EHRs, HIS, and data quality

• Smart hospitals, IoMT, robotics, sensor ecosystems

• Workflow and process mining

• Procurement, governance, and sustainability of health information systems

• Data provenance, auditability, and certification of data pipelines

• Green and energy-efficient digital health infrastructures

• Visual analytics and dashboards for health data

This track addresses health at population scale: surveillance and early warning, equity and global digital health, and the integration of climate, environmental, and One Health data into public-health intelligence.

• Digital surveillance, early-warning, and resilience systems

• Health equity, vulnerable populations, and global digital health

• Population-scale analytics and decision support

• Climate-health data integration and environmental monitoring

• One Health surveillance across human, animal, and ecosystem domains

• Sustainable health systems and planetary health action

• Digital twins for population modelling and scenario simulation

• Reproducible analytics frameworks and benchmarking resources

This track focuses on the people who deliver and receive care: patient-generated data and co-design, documentation and workflow, the technologies entering the consultation, and the education, wellbeing, and safety of the health workforce.

• mHealth, home monitoring, and patient-generated data

• Co-design, participatory approaches, and digital literacy

• Workflow, documentation, and care coordination solutions

• Ambient listening, speech technologies, and multimodal interfaces

• Workforce wellbeing, safety, and intelligent staffing analytics

• Digital health education and continuous professional development

• Digital identity and personal health record interoperability

• Human factors, cognitive load reduction, and user-interface safety

This track covers the design, validation, and safe clinical use of decision support and artificial intelligence, from responsible and lawful development to learning health systems that integrate evidence into practice.

• Responsible, ethical, and lawful AI (AI Act, MDR, EHDS alignment)

• GenAI assistants, agentic systems, multimodal models

• Human oversight, transparency, and explainability

• Explainable AI (XAI) methods and their clinical evaluation

• Clinical AI applications, risk prediction, diagnostics, treatment optimisation

• AI-enabled evidence integration and learning health systems

• Bias, calibration, clinical validity, and safety monitoring of models and algorithms

• Adversarial robustness, data and model poisoning defence, and drift detection

• Computable clinical guidelines, clinical knowledge graphs, and biomedical knowledge integration

• Liability, accountability, and regulatory compliance of AI in clinical use

Submissions in medical informatics and digital health that do not fall within a named

track.