Scientific Sessions

Digital neurology and artificial intelligence (AI) are rapidly transforming the way neurological disorders are diagnosed, monitored, and treated. Digital neurology leverages advanced technologies such as wearable devices, mobile health applications, and telemedicine platforms to collect real-time data on patients’ brain activity, motor functions, and cognitive performance. These tools enable continuous monitoring outside of clinical settings, providing clinicians with valuable insights into disease progression and treatment effectiveness. For example, wearable sensors can track tremors in Parkinson’s disease, while mobile apps can assess memory and attention in patients with Alzheimer’s disease. This digital integration not only enhances patient care but also empowers individuals to actively engage in managing their neurological health.

Artificial intelligence further strengthens digital neurology by analyzing large volumes of clinical and behavioral data to detect subtle patterns that might be overlooked by human observation. AI-powered algorithms are being applied in brain imaging for early detection of tumors, stroke, and neurodegenerative diseases, as well as in predictive models to anticipate disease progression and personalize treatment plans. Machine learning and deep learning techniques are also driving innovations in drug discovery, neuroimaging interpretation, and brain-computer interfaces that restore movement or communication in patients with paralysis. Despite challenges such as data privacy, standardization, and accessibility, the integration of AI in neurology holds enormous potential. By combining human expertise with digital and computational power, digital neurology and AI are paving the way for more precise, proactive, and patient-centered neurological care in the future.