AUTHOR=He Chunying , Hu Xiaohua , Wang Muren , Yin Xiaolan , Zhan Min , Li Yutong , Sun Linjuan , Du Yida , Chen Zhiyan , Wang Huan , Shao Haibin TITLE=Frontiers and hotspots evolution in mild cognitive impairment: a bibliometric analysis of from 2013 to 2023 JOURNAL=Frontiers in Neuroscience VOLUME=18 YEAR=2024 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2024.1352129 DOI=10.3389/fnins.2024.1352129 ISSN=1662-453X ABSTRACT=Background

Mild cognitive impairment is a heterogeneous syndrome. The heterogeneity of the syndrome and the absence of consensus limited the advancement of MCI. The purpose of our research is to create a visual framework of the last decade, highlight the hotspots of current research, and forecast the most fruitful avenues for future MCI research.

Methods

We collected all the MCI-related literature published between 1 January 2013, and 24 April 2023, on the “Web of Science.” The visual graph was created by the CiteSpace and VOSviewer. The current research hotspots and future research directions are summarized through the analysis of keywords and co-cited literature.

Results

There are 6,075 articles were included in the final analysis. The number of publications shows an upward trend, especially after 2018. The United States and the University of California System are the most prolific countries and institutions, respectively. Petersen is the author who ranks first in terms of publication volume and influence. Journal of Alzheimer’s Disease was the most productive journal. “neuroimaging,” “fluid markers,” and “predictors” are the focus of current research, and “machine learning,” “electroencephalogram,” “deep learning,” and “blood biomarkers” are potential research directions in the future.

Conclusion

The cognition of MCI has been continuously evolved and renewed by multiple countries’ joint efforts in the past decade. Hotspots for current research are on diagnostic biomarkers, such as fluid markers, neuroimaging, and so on. Future hotspots might be focused on the best prognostic and diagnostic models generated by machine learning and large-scale screening tools such as EEG and blood biomarkers.