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Artificial Intelligence-Enabled Devices in Neurology: Mapping the Present and Future
Ashwin Amurthur1,2, Davis James McCarthy3,4, Lee H Schwamm5
1Department of Neurology, Mass General Brigham, Boston, Massachusetts, United States.
Seminars in Neurology
|December 16, 2025
Summary
Artificial intelligence (AI) and machine learning (ML) medical devices are transforming neurologic care. This review analyzes 147 FDA-authorized devices and discusses their integration and future impact.
Area of Science:
- Neurology
- Medical Technology
- Artificial Intelligence
Background:
- The past decade has seen significant growth in AI and ML medical devices for neurology.
- These technologies are increasingly augmenting clinical workflows and patient care delivery.
Purpose of the Study:
- To review core machine learning techniques used in medical devices.
- To describe AI-enabled medical devices authorized by the FDA as of December 31, 2024.
- To analyze trends in device integration and implications for future neurologic care.
Main Methods:
- Introduction to fundamental machine learning techniques.
- Analysis of 147 AI-enabled medical devices with FDA authorization.
- Examination of integration trends and human-machine interaction models.
Main Results:
- 147 AI-enabled medical devices have received FDA authorization for neurology and neuroradiology indications.
- Key trends in clinical integration are identified.
- Emerging human-machine interaction models are highlighted.
Conclusions:
- AI and ML devices are reshaping neurologic care delivery.
- Understanding these technologies and their integration is crucial for future practice.
- Future neurologic care will likely involve advanced human-machine collaboration.
