The role of Artifical Intelligence (AI) in the management of nonmotor symptoms in Parkinson’s Disease

Abstract Artificial intelligence (AI) technologies are increasingly recognized as valuable tools to support the integrated management of Parkinson’s disease (PD), a progressive neurodegenerative disorder in which effective management, particularly in advanced stages, requires multidisciplinary collaboration across neurology, physiotherapy, speech therapy, psychiatry, and social care. While motor symptoms are central to diagnosis, nonmotor symptoms (NMS), such as cognitive decline, mood disorders, sleep disturbances, fatigue, pain, and autonomic dysfunction, contribute substantially to disease burden and reduced quality of life. AI can support the integration of care for PD. AI-powered systems can analyze complex datasets drawn from clinical teams, wearable devices, and patient-reported outcomes, enabling earlier detection of symptom changes, prediction of disease progression, and support for clinician decision-making. Furthermore, AI platforms can enhance patient self-management through personalized feedback and digital monitoring, while also improving communication between providers to deliver more coordinated and individualized care. This review examines the current and potential applications of AI in the management of NMS in PD, with a focus on cognitive, psychiatric, sleep-related, pain, and autonomic symptoms, highlighting its role in optimizing treatment strategies and improving patient outcomes.