ABSTRACT Background Artificial Intelligence (AI) is rapidly emerging as a transformative tool in medical research and practice. In neuro‐oncology, AI may help to enhance diagnostic accuracy and reproducibility, manage complex multi‐modal data, and facilitate personalized treatment. Methods This review aims to provide an overview of AI applications in the analysis of histopathological and molecular data of brain tumors. Results Key applications in histopathology include molecular biomarker prediction from H the lack of robust external validation in many published studies; and the limited model interpretability. These challenges are currently being tackled by efforts to compile multi‐institutional pathological datasets and by advances in explainable AI. Conclusions AI holds promise for advancing personalized neuro‐oncology by improving diagnostic accuracy and accelerating existing workflows. Its potential to democratize access to precision diagnostics hinges on efforts to reduce the costs of digital infrastructure and facilitate specialized training.
Roetzer‐Pejrimovsky et al. (Sun,) studied this question.