Utilization of Machine Learning to Guide Aneurysm Management

Introduction: Machine learning (ML) utilizes large input datasets to train computers algorithms that intelligently identify patterns to make predictions that has improved patient care in many areas of medicine. Here, we discuss the use of ML in vascular interventional radiology (VIR) to guide aneurysm management.

Method(s): We performed a literature review to understand all the therapeutic avenues utilizing ML within aneurysm management. We included articles that specifically focused on clinical applications in humans that have improved the care of all aneurysm patients. We stratified our results based on aneurysmal type and performed regression analysis to determine which ML techniques led to significantly improved patients.

Result(s): ML has improved image segmentation analysis to facilitate aneurysm detection and classification. ML shows impressive predictive capabilities for aneurysm risk, treatment planning, and patient prognosis. Finally, ML incorporation into mixed-reality platforms has led to enhanced procedural training.

Conclusion(s): ML implementation in our clinical workflows has unlocked new ways to improve aneurysm management. Understanding these avenues will accelerate clinical translation of ML into other domains of VIR.

Publikationsverlauf

Artikel online veröffentlicht:
09. Februar 2023