A Harvard Medical School-led team developed an artificial intelligence–powered diagnostic tool capable of distinguishing glioblastoma multiforme from visually similar brain tumors intraoperatively with unprecedented accuracy. This breakthrough equips surgeons with immediate, data-driven insights to tailor surgical decisions, potentially improving outcomes in neuro-oncology. The approach leverages real-time pathology data interpretation, representing a significant advancement in AI-assisted surgical oncology techniques.