Healthcare delivery is undergoing a profound transformation driven by two interconnected trends. The first is the digitization of the healthcare system, which has expanded opportunities for citizens and patients to access and contribute their own data – including patient-reported outcomes – and use digital technologies to manage their health and interact with healthcare professionals. This shift is often referred to as the healthcare system’s new digital front door, and redefines how healthcare services are accessed and delivered.

Simultaneously, the rise of artificial intelligence (AI) in healthcare is being fuelled by the vast amount of data generated by this digitization. AI is increasingly being used to support patients in managing their own health, as well as to assist healthcare professionals in the making of complex decisions. But as healthcare moves beyond physical locations and into digital spaces, critical questions emerge.

∙ How can we understand and design for a healthcare system no longer confined to hospitals and clinics?

∙ How can AI be harnessed to drive meaningful and lasting social impact, ensuring equal access and improved outcomes?

∙ What are the ethical considerations, risks, and challenges associated with AI-driven solutions, and how can they be responsibly addressed?

∙ What insights can we draw from recent advancements, and how can they inform the future of AI in health and beyond?

The theme of CSHI 2025, ‘AI for Social Good’, reflects these pressing questions, focusing on the role of AI and digital healthcare in promoting health, well-being, and equality. While some of the papers in this volume engage directly with this theme, others contribute to broader discussions on the design, implementation, and impact of socio-technical systems in healthcare.

This volume brings together cutting-edge research across the following themes:

∙ AI-driven decision support and usability in healthcare

∙ EHR implementation, usability, and evolution

∙ Human-centred AI and health informatics

∙ Clinician experiences, health-data interpretation, and medication safety

∙ AI in simulation, screening, and clinical trials.

The discussions and findings presented in these proceedings reflect the depth and diversity of research in this rapidly evolving field. We hope they will serve as a valuable resource for researchers, practitioners, and policymakers, fostering further dialogue and collaboration on the future of AI in healthcare.