Artificial intelligence (AI) is providing several tools in revolutionising treatment options in neuro-oncology, especially in the context of astrocytoma detection and management, highlights a recently published study.The study titled ‘Implication of artificial intelligence on astrocytoma detection and treatment’ and published on QScience.com notes that AI and deep learning techniques have significantly advanced the diagnostic process of these diseases. These techniques enable more accurate tumour grading and classification through comprehensive analysis of histopathological images.Astrocytoma, a neoplasm arising from glial cells in the central nervous system can be categorised as either slow-growing or aggressive based on tumour grade. Tumour grading is crucial in determining prognosis and clinical course.AI-powered tools, such as convolutional neural networks, assist in distinguishing between tumour subtypes, while radiomics and computer vision improve real-time intraoperative decision-making, thereby aiding neurosurgeons to optimise surgical resections with greater precision.The study by a group of researchers from various countries in the Arab region says that in terms of treatment, AI facilitates personalised therapy by integrating genomic, radiological, and clinical data to tailor treatment strategies based on individual tumour profiles. They state that prognostic models using AI have demonstrated up to 80% accuracy in predicting patient outcomes, guiding oncologists in selecting the most effective interventions."AI-driven tumour segmentation enhances radiotherapy precision by accurately identifying organs at risk, thereby reducing radiation exposure to healthy tissues. Moreover, AI contributes to drug discovery by accelerating the identification of novel therapeutic compounds with high blood–brain barrier permeability," remarked the researchers.An ideal AI-driven diagnostic system in neuro-oncology would integrate imaging, clinical, and molecular data to accurately classify newly diagnosed tumour subtypes, thereby advancing precision medicine and enabling personalised treatment modifications, continues the study.According to the study, the clinical integration of advanced AI technologies into the field of neuro-oncology, including computer vision, machine learning, and augmented or virtual reality has led to the development of highly effective tools for managing brain and spinal tumours. AI contributes to improved patient care across all stages of neuro-oncological management, from planning to pathological identification, as well as post-operative feedback.However, the research points out despite these advancements, several challenges hinder AI’s clinical integration, including data privacy concerns, algorithmic bias, and the need for regulatory frameworks to ensure equitable and ethical AI applications in healthcare. It suggests the health sector must establish standardised AI protocols, invest in AI-compatible infrastructure, and integrate AI-driven decision support systems into clinical workflows to bridge the gaps. Additionally, interdisciplinary collaboration between AI specialists, radiologists, and oncologists is essential to validate AI models through large-scale multicenter studies and randomised controlled trials.The study also emphasises that future research should focus on expanding AI accessibility in resource-limited settings and addressing ethical concerns through transparent AI governance. By implementing structured mechanisms for AI adoption, the healthcare sector can harness its full potential to revolutionise astrocytoma management, ultimately improving diagnostic accuracy, treatment efficacy, and patient outcomes.