Related Experiment Video
Updated: Jun 13, 2025

Implementation of Minimally Invasive Brain Tumor Resection in Rodents for High Viability Tissue Collection
Published on: May 9, 2022
Emerging Trends in Artificial Intelligence in Neuro-Oncology
Saahil Chadha1,2, Durga V Sritharan1,2, Thomas Hager1,2
1Department of Therapeutic Radiology, Yale School of Medicine, 330 Cedar St, New Haven, CT, 06519, USA.
Purpose Of Review:
This article explores the evolving role of artificial intelligence (AI) in neuro-oncology, highlighting its potential to enhance diagnostic accuracy, predict patient outcomes, optimize treatment planning, and streamline clinical workflows.
Recent Findings:
AI applications have led to significant advancements in automated tumor segmentation, molecular classification, risk stratification, treatment response evaluation, and computational pathology. AI-driven innovations have also accelerated drug discovery and leveraged natural language processing to generate structured clinical reports and extract actionable insights from unstructured data. AI has transformative potential in neuro-oncology; however, challenges like data quality, model generalizability, and clinical integration persist. Overcoming these barriers may involve new computational techniques and hardware efficiencies, as well as raising awareness, fostering interdisciplinary education, and expanding access to AI-driven tools.
Related Concept Videos
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Current Trends in Nursing II

