The field of AI-assisted clinical practice and research is rapidly evolving, with a focus on developing innovative solutions to improve clinical efficiency, accuracy, and patient care. Recent developments have centered around the use of generative AI, mixed-initiative systems, and human-centered AI agents to support tasks such as documentation, sensemaking, and decision making. These advancements have shown significant promise in reducing physician workload, improving the quality of systematic reviews, and enhancing the interpretability of complex data. Noteworthy papers in this area include:

• ScholarMate, which introduced a mixed-initiative tool for qualitative knowledge work and information sensemaking,
• InsightAgent, which demonstrated the ability to complete systematic reviews in hours instead of months with interactive AI agents,
• DataScout, which developed an automatic data fact retrieval system for statement augmentation with an LLM-Based agent. Overall, the field is moving towards more collaborative and transparent AI systems that can effectively support human clinicians and researchers in their work.