Launched in 2016, the Health Recommender Systems Workshop (HealthRecSys) rapidly became a central forum for discussing the transformative capabilities of personalized recommender systems within the health and care sectors. Despite the unforeseen pause due to the COVID-19 pandemic and other challenges, the workshop’s influence persisted through its vibrant community and publications. Our aim with the 6th HealthRecSys is to reignite these conversations and provide a forward-thinking platform that revisits the foundational elements that have contributed to the field’s growth. However, the workshop aspires to do more by infusing new perspectives and tackling the most pressing global challenges and technological innovations head-on with contemporary themes such as the impact of global health crises, generative AI models, personalized and self-managed care, and the increasing focus on health equity. HealthRecSys is dedicated to strengthening the network of researchers working on health recommender systems, drawing participants from an array of health and care domains. Through our combined interactive and paper based workshop format, we aim at cultivating a cross-disciplinary community that promotes collaboration among recommender systems specialists, healthcare professionals, ethicists, and policymakers, among others.@en

People increasingly use the Internet for obtaining information regarding diseases, diagnoses and available treatments. Currently, many online health portals already provide non-personalized health information in the form of articles. However, it can be challenging to find information relevant to one's condition, interpret this in context, and understand the medical terms and relationships. Recommender Systems (RS) already help these systems perform precise information filtering. In this short paper, we look one step ahead and show the progress made towards RS helping users find personalized, complex medical interventions or support them with preventive healthcare measures. We identify key challenges that need to be addressed for RS to offer the kind of decision support needed in high-risk domains like healthcare.@en