Role of Machine Learning and Artificial Intelligence in Interventional Oncology

Area of Science:

• Oncology
• Medical Imaging
• Artificial Intelligence

Background:

• Artificial intelligence (AI) and machine learning (ML) are rapidly advancing in medicine.
• Interventional oncology can significantly benefit from AI/ML for image analysis and procedural guidance.

Purpose of the Study:

• To review the current applications of AI and ML in interventional oncology.
• To discuss the potential impact and limitations of these technologies in the field.

Main Methods:

• Literature review of AI and ML applications in interventional oncology.
• Analysis of AI/ML's role in cancer detection, diagnosis, treatment selection, and intraprocedural guidance.

Main Results:

• AI/ML can improve cancer detection and diagnostic accuracy.
• These technologies aid in predicting treatment outcomes and optimizing treatment selection.
• AI/ML enhances intraprocedural guidance through improved needle tracking and image fusion.

Conclusions:

• AI and ML show great potential to advance interventional oncology and cancer care.
• Challenges include data management, model validation, workflow integration, and ethical considerations.