The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025, at the University of California, Berkeley, in Berkeley, California, USA. As part of this year's program, we hosted Research Roundtables to catalyze collaborative, small-group dialogue around critical, timely topics at the intersection of machine learning and healthcare. Each roundtable was moderated by a team of senior and junior chairs who fostered open exchange, intellectual curiosity, and inclusive engagement. The sessions emphasized rigorous discussion of key challenges, exploration of emerging opportunities, and collective ideation toward actionable directions in the field. In total, eight roundtables were held by 19 roundtable chairs on topics of "Explainability, Interpretability, and Transparency," "Uncertainty, Bias, and Fairness," "Causality," "Domain Adaptation," "Foundation Models," "Learning from Small Medical Data," "Multimodal Methods," and "Scalable, Translational Healthcare Solutions."

翻译：第六届健康、推断与学习年度会议（CHIL 2025）由健康学习与推断协会主办，于2025年6月25日至27日在美国加利福尼亚州伯克利市的加州大学伯克利分校线下举行。作为今年会议议程的一部分，我们组织了研究圆桌会议，旨在围绕机器学习与医疗保健交叉领域的关键、前沿议题，推动协作式的小组对话。每个圆桌会议由资深与初级主席组成的团队主持，促进开放交流、激发学术好奇心并鼓励包容性参与。会议环节重点聚焦于对关键挑战的严谨讨论、对新兴机遇的探索，以及对该领域可行动方向的集体构思。总计由19位圆桌主席主持了八场圆桌会议，议题涵盖“可解释性、可理解性与透明度”、“不确定性、偏见与公平性”、“因果推断”、“领域自适应”、“基础模型”、“小规模医疗数据学习”、“多模态方法”以及“可扩展、可转化的医疗解决方案”。