Clinical Artificial Intelligence Applications in Radiology: Neuro.

Area of Science:

• Neuroradiology
• Medical Imaging
• Artificial Intelligence

Background:

• Radiologists are leading medical digitization.
• Artificial intelligence (AI) shows significant promise in medical imaging.
• AI applications in neuroradiology are rapidly expanding.

Purpose of the Study:

• To illustrate current AI applications in neuroradiology.
• To review machine learning challenges specific to neuroradiology.
• To discuss the Centers for Medicare and Medicaid Services (CMS) reimbursement for AI in stroke detection.

Main Methods:

• Review of existing literature on AI in neuroradiology.
• Discussion of machine learning challenges.
• Analysis of CMS reimbursement policies for AI algorithms.

Main Results:

• Numerous AI applications are emerging in neuroradiology.
• Significant machine learning challenges exist within neuroradiology.
• CMS has approved reimbursement for an AI algorithm for large vessel occlusion stroke detection.

Conclusions:

• AI is a key area of innovation in neuroradiology.
• Addressing machine learning challenges is crucial for AI advancement.
• Reimbursement approval signifies growing acceptance of AI in clinical practice.