Healthcare AI

Mapping knowledge landscapes and emerging trends of artificial intelligence in the early screening of cognitive impairment diseases

Objective: To comprehensively analyze the research status of artificial intelligence in the early screening of cognitive impairment diseases by using bibliometric methods, clarify the shifts in research hotspots, core research teams, and the distribution of major research institutions, fill the gap in the combing of research contexts, improve the research system framework from basic theory to clinical application, and lay the foundation for subsequent research. Method: Taking the Web of Science as the retrieval source, the search formula was determined by integrating terms related to artificial intelligence, terms related to cognitive impairment diseases, and terms related to early screening. The relevant research literatures published from the establishment of the database to March 2025 were retrieved, and the bibliometric software CiteSpace and Vosviewer were used to conduct bibliometric analysis of the literatures. Results: A total of 907 literatures were included. The early research focused on linear discriminant analysis, etc., and in recent years, it has shifted to feature extraction, explainable artificial intelligence, etc. Fields such as multimodal data fusion have received attention, and interdisciplinary cooperation has become a potential hotspot. Conclusion: Artificial intelligence has developed rapidly in the field of early screening of cognitive impairment. The United States and China have made outstanding achievements and have advantages in basic research and industrialization respectively. In the future, international exchanges and cooperation should be strengthened, research differences among different countries should be compared, and multiple databases should be used for research to promote the development of this field, improve the early diagnosis rate of cognitive impairment, and improve medical services.