Application of Artificial Intelligence on Neurodegenerative Disorder Care: A Scoping Review

Abstract

Background: Neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis, involve progressive neuronal degeneration, resulting in cognitive and functional impairments. The rising prevalence of these conditions highlights the potential of artificial intelligence (AI) as an innovative tool to advance their diagnosis and management. Objectives: To evaluate the current applications of AI in the diagnosis, management, and treatment of neurodegenerative diseases Methods: Following the Arksey and O’Malley framework for scoping reviews, this review involved a systematic search of literature across four databases, including CINAHL, PubMed, Science Direct, and Google Scholar, published from 2020 to 2025. Studies related to AI in neurodegenerative disorders were selected based on diagnostics, treatment, patient care, and AI technologies, with 20 articles included in the review. Results: The scoping review identified five key applications of AI in the care and management of neurodegenerative disorders: (1) Diagnostic advancement, (2) Predictive modeling, (3) Drug discovery, (4) Clinical trial enhancement, and (5) Personalized medicine. AI has demonstrated remarkable potential in early detection by analyzing complex datasets. These include medical imaging, genetics, and clinical records, which help identify disease markers and predict progression. Predictive modeling aids disease trajectory assessment and personalized care planning. AI accelerates drug discovery by identifying therapeutic targets and addressing the complexity of these diseases. It also enhances clinical trial efficiency by optimising design and data analysis. AI-driven personalised medicine can offer tailored treatments to individual patient profiles, improved therapeutic outcomes, and minimise adverse effects. Conclusions: AI has a significant impact on the care and management of neurodegenerative disorders, enhancing diagnostics, predictive modeling, drug discovery, clinical trials, and personalised medicine. Its ability to analyse complex data accelerates early detection and treatment planning, ultimately improving patient outcomes and optimising therapeutic strategies. However, ethical concerns, data privacy, and potential biases must be addressed. Continued research and interdisciplinary collaboration are key to unlocking full potential of AI responsibly.