Minisymposium Presentation

Advanced AI systems like LLMs and LMMs are transforming medical applications, but face adoption barriers in clinical settings. This panel will discuss the challenges and solutions to develop reliable, multitask clinical AI agents and integrating them into hospital infrastructure.

Discussion Points:+ Current challenges: task-specific limitations, knowledge integration gaps, single-modality constraints, and reasoning deficiencies+ Capabilities of foundation models for multitask medical applications (classification, segmentation, reporting)+ Challenges to clinical implementation: 1. Knowledge integration: Embedding biomedical expertise into AI systems. 2. Multimodal integration: Combining imaging, text, and diverse data streams. 3. Evidence grounding: Ensuring outputs are verifiable and trustworthy. 4. Technical feasibility: Optimizing models to run efficiently on standard hospital infrastructure. 5. Workflow integration: Bridging research innovations to practical clinical use.