神经外科学专业英语

Gliomas are among the most common and heterogeneous primary tumours of the central nervous system. Accurate grading is essential for treatment planning and prognosis, yet conventional histopathological approaches are limited by subjectivity and poor reproducibility. This study aimed to develop a machine learning–based prediction model that integrates clinical and molecular characteristics to improve early glioma grading, thereby enhancing diagnostic accuracy and supporting individualized treatment strategies.