A team led by Harvard Medical School unveiled an AI-based tool capable of distinguishing glioblastoma from visually similar brain tumors intraoperatively with high accuracy. This advancement promises to improve surgical decision-making by providing immediate tumor classification, which is crucial given glioblastoma’s aggressive nature and diagnostic complexity. Published in Nature Communications, the study complements other molecular insights into glioma treatment responses involving helicases RECQL4 and BLM, delineating their separate and overlapping roles in chemotherapy sensitivity.