Application of Knowledge Graphs in Neurodegenerative Diseases: A Brief Literature Review

Knowledge graphs (KGs) constitute a fundamental tool in biomedical research, offering new perspectives for integrating information from different sources. This allows for a more comprehensive and effective understanding of the study and treatment of neurodegenerative diseases. This work aims to present a brief literature review demonstrating how KGs have been used in this field. It will cover the main concepts, the most analyzed disease-related data, and the principal neurodegenerative diseases to which this technology is applied. This review showed that Alzheimer's disease has been the most frequently modeled condition in KGs. The most analyzed data are clinical trial results and treatments, which provide a deeper understanding of the disease. We conclude that no exists (KGs) specifically for
Ataxia Spinocerebellar type 2. Furthermore, the knowledge graph significantly improves the accuracy of prediction and treatment for these diseases. Additionally, concepts should be integrated for modeling data related to motor incoordination, balance issues, speech difficulties, and, in some cases, cognitive problems.