Artificial Intelligence in Brain Tumor Management: Evidence, Clinical Use, and Implications for PA Practice

Authors

• Helen French, University of LynchburgFollow

Specialty

Neurosurgery

Advisor

Dr. Bolander

Abstract

Artificial intelligence (AI) is increasingly influencing clinical decision-making in brain tumor management, with applications spanning diagnosis, prognostication, and intraoperative support in neurosurgical care. Current evidence demonstrates that AI-based imaging tools improve tumor detection, segmentation, and non-invasive molecular characterization, enabling integrative prognostic modeling that supports individualized risk stratification and surgical planning. Emerging intraoperative applications, including real-time navigation and rapid histopathologic analysis, suggest potential improvements in surgical precision and reductions in complication rates, although most systems remain in early stages of clinical validation. Despite these advances, clinical translation is limited by insufficient prospective validation, restricted generalizability, and unresolved concerns regarding bias, transparency, and workflow integration. This review synthesizes current evidence to clarify where AI meaningfully informs neurosurgical decision-making and where further validation is required to support safe, equitable clinical adoption.

Recommended Citation

French H. Artificial Intelligence in Brain Tumor Management: Evidence, Clinical Use, and Implications for PA Practice. University of Lynchburg DMSc Doctoral Project Assignment Repository. 2026; 8(1).