Research Trends in Application of Artificial Intelligence in Alzheimer’s Disease: Bibliometric and Visualization Analysis

Abstract

The remarkable performance of Artificial Intelligence (AI) in the diagnosis and prediction of Alzheimer’s disease (AD) has attracted considerable attention in recent years. This study intends to outline the development trends and research focus in the AI-Alzheimer field. The VOSviewer and bibliometrix R software package are employed for bibliometrics and visualization analysis of literature obtained from the Web of Science Core Collection database. There are 5,991 affiliations from 104 countries/regions that published 5,675 articles in this field by 2023. Results demonstrate that the number of AIAlzheimer-related publications has experienced slow progress for over twenty years before entering a period of exponential growth in 2016. The United States and China, contributing over 54% of the publications, stand out as leaders in technological innovation and international cooperation. The clustering analysis of keywords indicates that the major research domains are the utilization of machine learning and deep learning algorithms for AD and mild cognitive impairment (MCI) classification, early diagnosis of disease, and drug discovery. Generative adversarial networks (GANs), transfer learning, and Transformers are the emerging AI algorithms applied in the field of Alzheimer’s research, which also represent promising directions for future investigation. The findings provide a comprehensive summary of the AI-Alzheimer field and identify research frontiers, offering valuable references for scholars.

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