IFCN position statement: use of artificial intelligence in clinical neurophysiology

In recent years, artificial intelligence (AI) has made significant strides, gaining traction across various domains, including clinical medicine. The integration of AI as a decision-support tool introduces complexities, particularly in ensuring patient safety and upholding clinical accountability. This is especially pertinent in clinical neurophysiology (CNP), where AI shows promise in enhancing the interpretation of neurophysiologic data from modalities such as electroencephalography, electromyography, and others. Recognizing the potential and inherent challenges of AI integration, the International Federation of Clinical Neurophysiology (IFCN) has set forth guidelines to steer the responsible development, evaluation, and application of AI technologies in CNP. The IFCN's core position on AI in CNP emphasizes improving healthcare outcomes, prioritizing patient-centered care, maintaining transparency in AI-generated interpretations, and supporting, rather than replacing, clinical expertise. As AI technology evolves, the IFCN stresses that models implemented in clinical practice, especially when lacking supervision by experts must meet stringent standards for accuracy, safety, and quality control, and that AI cannot substitute expert care without adequate oversight. The successful integration of AI in CNP hinges on dataset diversity, transparent and ethical training practices, and balancing model complexity with real-world validation. Continuous performance monitoring and clinician feedback are vital to maintaining AI system reliability over time. The IFCN envisions a future where AI ethically enhances CNP practice through multidisciplinary collaboration, focusing on patient safety, clinical integrity, and scientific rigor. Properly implemented, AI can revolutionize CNP by offering real-time decision support, personalized interventions, and remote monitoring, thus advancing the quality of care in CNP.