Abstract

Moh Aijaz, Ramesh Kumar A., Shmmon Ahmad, Md Shams Raja, Rajneesh Kumar Gupta and Rajarshi Yadav*

ABSTRACT

Parkinson's Disease (PD) impacts millions worldwide with both motor and non-motor symptoms. Traditional diagnostic methods often miss early signs, delaying treatment. However, recent developments in Artificial Intelligence (AI) offer new hope. AI can now aid in early detection, continuous monitoring, and tailored treatment of PD. Techniques like machine learning and deep learning can be examined through complex data to find early PD signs, enhancing diagnostic accuracy. AI-driven imaging can recognize subtle brain changes tied to PD, and wearable tech provides real-time updates on symptoms and disease progression. Predictive analytics help adjust treatments as needed, whereas AI-based plans improve effectiveness and reduce side effects. AI also accelerates drug discovery and finds new uses for existing drugs. Besides clinical benefits, AI tools like virtual assistants and chatbots improve patient engagement and self-care, and remote monitoring makes healthcare more accessible. AI also helps caregivers with practical insights and recommendations. Despite these advances, challenges such as data privacy, biases in algorithms, and transparency issues remain. Ensuring AI tools are accessible and affordable is crucial to prevent deteriorating health disparities. This review looks at how AI is shaping PD management, considering its technological, ethical, and social impacts to better patient outcomes.