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.
