Artificial intelligence in neurodegenerative disease diagnosis: Advancing Alzheimer's and Parkinson's diseases
Article
Chandru, M, Abinesh, M, Ananth, M Siva et al. (2026). Artificial intelligence in neurodegenerative disease diagnosis: Advancing Alzheimer's and Parkinson's diseases
. Current Opinion in Biomedical Engineering, 37 10.1016/j.cobme.2025.100638
Chandru, M, Abinesh, M, Ananth, M Siva et al. (2026). Artificial intelligence in neurodegenerative disease diagnosis: Advancing Alzheimer's and Parkinson's diseases
. Current Opinion in Biomedical Engineering, 37 10.1016/j.cobme.2025.100638
This review article explores the significant advancements of artificial intelligence (AI) as a transformative tool for the early detection of major neurodegenerative diseases, specifically Alzheimer’s disease (AD) and Parkinson’s disease (PD). Traditional diagnostic techniques, including standardized clinical cognitive assessments, molecular biomarker analysis, and neuroimaging, remain crucial in clinical assessment. However, their utility is often limited by their accessibility, cost, and insufficient sensitivity. In the recent years, AI-driven techniques have emerged as a promising tool in advancing the early detection of AD and PD. These techniques play a crucial role in diagnosis by analyzing complex dataset derived from neuroimaging, integrated wearable sensors, and various digital biomarkers. By integrating multimodal data analysis with digital phenotyping and digital biomarkers discovery, a personalized therapeutic regime can be developed. Challenges, including the need for standardized data acquisition, improving model interpretability, and addressing ethical concerns related to data privacy and equitable access, are also highlighted.
