Brain tumors present a daunting clinical challenge, necessitating unwavering innovation in diagnostics, imaging, and therapeutics. Emerging advances in artificial intelligence (AI), molecular biomarkers, and neuroimaging have transformed the research landscape.

The current research conducted bibliometric analysis to map global research trends in brain tumor diagnosis, imaging, and treatment strategies between 2023-2025, with a particular focus on AI applicability and biomarker-driven precision medicine.

A systematic literature search of the Scopus database was performed in July 2025 for English original research articles between 2023 and 2025. The search keywords included: "brain tumor," "glioma," "glioblastoma," "meningioma," "astrocytoma," "diagnosis," "MRI," "CT," "artificial intelligence," "deep learning," "machine learning," "radiotherapy," "chemotherapy," "surgery," "biomarkers," "prognosis," "segmentation," and "classification." Bibliographic data were analyzed using Biblioshiny to explore publication output, citation impact, prominent authors, institutional productivity, keyword trends, and collaboration networks.

The analysis included 23,496 papers from over 93,000 researchers. It indicated a research boom in AI-enhanced diagnostics, radiomics, and individualized treatments. Both China and the U.S. were leading producers, but the U.S. recorded greater international collaboration and citation impact. Glioma classification, MRI-based segmentation, and deep learning applications were the most common topics. Collaboration networks were geographically focused, with a particular concentration in East Asia.

Brain tumor research is rapidly moving towards precision and AI-driven strategies. While there is a growing scientific output, more international and intersectoral collaboration is needed to make these advances translate to equitable clinical gain.