Emerging Trends in Artificial Intelligence in Neuro-Oncology

Area of Science:

• Neuroscience
• Oncology
• Computer Science
• Medical Imaging

Background:

• Artificial intelligence (AI) is increasingly integrated into medical fields.
• Neuro-oncology involves complex diagnosis and treatment of brain tumors.
• There is a growing need for advanced tools to manage neuro-oncology data and improve patient outcomes.

Purpose of the Study:

• To explore the evolving role and applications of AI in neuro-oncology.
• To highlight AI's potential in enhancing diagnostic accuracy and predicting patient outcomes.
• To discuss AI's role in optimizing treatment planning and streamlining clinical workflows.

Main Methods:

• Review of current AI applications in neuro-oncology.
• Analysis of AI's impact on tumor segmentation, molecular classification, and risk stratification.
• Examination of AI's use in drug discovery and natural language processing for clinical data.

Main Results:

• AI has significantly advanced automated tumor segmentation, molecular classification, and risk stratification.
• AI accelerates drug discovery and utilizes natural language processing for structured clinical reports.
• Challenges such as data quality, model generalizability, and clinical integration persist.

Conclusions:

• AI holds transformative potential for neuro-oncology, improving various aspects of patient care.
• Overcoming barriers requires new computational techniques, hardware efficiencies, and interdisciplinary collaboration.
• Increased awareness, education, and access to AI tools are crucial for widespread adoption.