[Artificial intelligence technologies in clinical neurooncology]

Area of Science:

• Neuroscience
• Oncology
• Computer Science

Background:

• 21st-century neurooncology integrates diverse neuroscientific findings.
• Clinical neurooncology generates complex data requiring advanced analytical methods.
• Artificial intelligence (AI) is a rapidly developing field with potential applications in medicine.

Approach:

• This review examines the potential and applications of AI in neurooncology.
• The focus is on AI's role in understanding and treating glial tumors.
• The review synthesizes current knowledge on AI in neurooncology.

Key Points:

• AI enables sophisticated mathematical modeling and predictive analytics.
• AI technologies can uncover new scientific insights from complex neurooncology data.
• Applications are particularly relevant for neuro-oncological conditions like glial tumors.

Conclusions:

• AI holds significant promise for advancing neurooncology.
• The insights gained from AI in neurooncology may extend to other clinical fields.
• Further development and integration of AI are crucial for future neurooncology research and practice.