Team Name REAiHL Lab Track Health care & Life Sciences Use Case We are developing a transparent validation framework for ambient AI scribe applications — AI systems that automatically capture and summarize clinical conversations to reduce administrative burden for healthcare professionals.   Although these tools have great potential to transform healthcare, research shows that only 2% of AI projects make it to the bedside. Closing this gap requires responsible and trustworthy validation of developed AI models.   Our framework evaluates both performance (e.g., accuracy, comprehensiveness) and ethical dimensions (e.g., fairness, impact on the patient–clinician relationship) of ambient AI scribe applications. Using techniques such as sentiment analysis and LLM-as-a-judge, and powered by SAS technology, we compute these metrics and present them in a clear, intuitive dashboard.   The dashboard gives evaluators an at-a-glance overview of strengths, risks, and trade-offs, making AI evaluation both transparent and actionable. To further enhance usability, we are also exploring the integration of an explanatory LLM that provides contextual insights and interprets the results displayed. Technology SAS Viya (SAS Studio, SAS Visual Analytics, python) Region EMEA Team lead Imke Bloemen Team members Imane Ihaddouchen, Emma Jane Spencer, Willemijn Berkhout, Julia van Wijngaarden Social media handles *all team members' social media links here* Is your team interested in participating in an interview? Y Optional: Expand on your technology expertise We are the REAiHL Lab, a multidisciplinary team united by a shared mission: bridging the implementation gap in AI for healthcare through responsible evaluation. Our team brings together expertise in medical engineering, data science and AI, and AI ethics, combining technical depth with a strong focus on clinical relevance and trustworthiness. With experience in building ICU dashboards using SAS software, we are skilled at turning complex data into clear, actionable insights for healthcare professionals. In this hackathon, we aim to extend this expertise to create a broadly applicable tool for ambient AI scribe validation in healthcare, powered by SAS software, combined with innovative technologies such as LLM-as-a-judge.   By combining our diverse backgrounds and shared ambition, we are well-positioned to deliver solutions that ensure AI is transparent and trustworthy, making ambient AI scribes truly usable at the bedside.   ... View more