# OpenTumorBoard

Researchers curated OpenTumorBoard from 219 recorded tumor board meetings totaling 12,534 minutes of YouTube video, yielding 611 patient cases, 19,157 discussion turns and ten specialist roles, and used it for two tasks—single Specialist Turn responses and full Board Simulation—finding that across 14 general-purpose and medical LLMs the best model reached only 3.43/5 in clinical equivalence and 2.78/5 in alignment with true board conclusions, while supervised finetuning plus reinforcement learning on Qwen2.5-VL-3B raised conclusion alignment from 1.58 to 1.86.

Researchers curated OpenTumorBoard from 219 recorded tumor board meetings totaling 12,534 minutes of YouTube video, yielding 611 patient cases, 19,157 discussion turns and ten specialist roles, and used it for two tasks—single Specialist Turn responses and full Board Simulation—finding that across 14 general-purpose and medical LLMs the best model reached only 3.43/5 in clinical equivalence and 2.78/5 in alignment with true board conclusions, while supervised finetuning plus reinforcement learning on Qwen2.5-VL-3B raised conclusion alignment from 1.58 to 1.86.