Document Type : Review Article
Authors
1 1. Neuroscience research center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2. Department of neurosurgery, Alborz university, Karaj, Iran.
2 Sean M Healey & AMG Center for ALS, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Abstract
Background: Amyotrophic lateral sclerosis (ALS) is a progressive, incurable neurodegenerative disease. ALS databases play a critical role in supporting research, decision-making, and the development of generative machine learning (ML) applications. This scoping review aims to explore genetic/imaging/facial expression/ voice databases that can inform ALS disease research, supporting future multi-modal ML applications.
Methods: A literature search was conducted across PubMed, Scopus, Web of Science, Cochrane Library, and grey literature, covering publications up to September 2025. The PRISMA-ScR guidelines were followed. Two reviewers independently screened titles, abstracts, and full texts. Databases were included if they provided ALS-specific data on genomics, medical imaging, voice, or facial expression. Extracted information included data type, accessibility, demographic details, key features, limitations, and database link. This review identifies gaps in the current database landscape. The Newcastle-Ottawa scale (NOS) was used for evaluating study quality.
Results: Twenty-four ALS databases were identified, accounting for twenty studies of moderate quality. Most resources are single-modality, with only a few (e.g., SALSA-SGC, Answer ALS, CALSNIC) offering multi-dimensional data. Common limitations include restricted demographic diversity, small sample sizes in digital cohorts, limited longitudinal follow-up, and insufficient cross-modal integration. Data gaps limit the development of accurate ML models in ALS.
Conclusion: This scoping review provides a comprehensive understanding of ALS databases for future multi-modal deep learning research. Research gaps were highlighted, and recommendations for future directions were stated.
Graphical Abstract
)
Keywords
Main Subjects
)