Bibliometric analysis of electroencephalogram research in Parkinson's disease from 2004 to 2023.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder affecting millions globally. It encompasses both motor and non-motor symptoms, with a notable impact on patients' quality of life. Electroencephalogram (EEG) is a non-invasive tool that is increasingly utilized to investigate neural mechanisms in PD, identify early diagnostic markers, and assess therapeutic responses. The data were sourced from the Science Citation Index Expanded within the Web of Science Core Collection database, focusing on publications related to EEG research in PD from 2004 to 2023. A comprehensive bibliometric analysis was conducted using CiteSpace and VOSviewer software. The analysis began with an evaluation of the selected publications, identifying leading countries, institutions, authors, and journals, as well as co-cited references, to summarize the current state of EEG research in PD. Keywords are employed to identify research topics that are currently of interest in this field through the analysis of high-frequency keyword co-occurrence and cluster analysis. Finally, burst keywords were identified to uncover emerging trends and research frontiers in the field, highlighting shifts in interest and identifying future research directions. A total of 1,559 publications on EEG research in PD were identified. The United States, Germany, and England have made notable contributions to the field. The University of London is the leading institution in terms of publication output, with the University of California closely following. The most prolific authors are Brown P, Fuhr P, and Stam C In terms of total citations and per-article citations, Stam C has the highest number of citations, while Brown P has the highest H-index. In terms of the total number of publications, Clinical Neurophysiology is the leading journal, while Brain is the most highly cited. The most frequently cited articles pertain to software toolboxes for EEG analysis, neural oscillations, and PD pathophysiology. Through analyzing the keywords, four research hotspots were identified: research on the neural oscillations and connectivity, research on the innovations in EEG Analysis, impact of therapies on EEG, and research on cognitive and emotional assessments. This bibliometric analysis demonstrates a growing global interest in EEG research in PD. The investigation of neural oscillations and connectivity remains a primary focus of research. The application of machine learning, deep learning, and task analysis techniques offers promising avenues for future research in EEG and PD, suggesting the potential for advancements in this field. This study offers valuable insights into the major research trends, influential contributors, and evolving themes in this field, providing a roadmap for future exploration.

Liao XY ，Gao YX ，Qian TT ，Zhou LH ，Li LQ ，Gong Y ，Ye TF ... -  《Frontiers in Neuroscience》

Research Trends in the Application of Artificial Intelligence in Oncology: A Bibliometric and Network Visualization Study.

The past decade has seen major advances in the use of artificial intelligence (AI) to solve various biomedical problems, including cancer. This has resulted in more than 6000 scientific papers focusing on AI in oncology alone. The expansiveness of this research area presents a challenge to those seeking to understand how it has developed. A scientific analysis of AI in the oncology literature is therefore crucial for understanding its overall structure and development. This may be addressed through bibliometric analysis, which employs computational and visual tools to identify research activity, relationships, and expertise within large collections of bibliographic data. There is already a large volume of research data regarding the development of AI applications in cancer research. However, there is no published bibliometric analysis of this topic that offers comprehensive insights into publication growth, co-citation networks, research collaboration, and keyword co-occurrence analysis for technological trends involving AI across the entire spectrum of oncology research. The purpose of this study is to investigate documents published during the last decade using bibliometric indicators and network visualization. This will provide a detailed assessment of global research activities, key themes, and AI trends over the entire breadth of the oncology field. It will also specifically highlight top-performing authors, organizations, and nations that have made major contributions to this research domain, as well as their interactions via network collaboration maps and betweenness centrality metric. This study represents the first global investigation of AI covering the entire cancer field and using several validated bibliometric techniques. It should provide valuable reference material for reorienting this field and for identifying research trajectories, topics, major publications, and influential entities including scholars, institutions, and countries. It will also identify international collaborations at three levels: micro (that of an individual researcher), meso (that of an institution), and macro (that of a country), in order to inform future lines of research. The Science Citation Index Expanded from the Web of Science Core Collection was searched for articles and reviews pertaining exclusively to AI in cancer from 2012 through 2022. Annual publication trends were plotted using Microsoft Excel 2019. CiteSpace and VOSViewer were used to investigate the most productive countries, researchers, journals, as well as the sharing of resources, intellectual property, and knowledge base in this field, along with the co-citation analysis of references and keywords. A total of 6757 documents were retrieved. China produced the most publications of any country (2087, 30.89%), and Sun Yat Sen University the highest number (167, 2.47%) of any institute. WEI WANG was the most prolific author (33, 0.49%). RUI ZHANG ranked first for highest betweenness centrality (0.21) and collaboration criteria. Scientific Reports was found to be the most prolific journal (208, 3.18%), while PloS one had the most co-citations (2121, 1.55%). Strong and ongoing citation bursts were found for keywords such as "tissue microarray", "tissue segmentation", and "artificial neural network". Deep learning currently represents one of the most cutting-edge and applicable branches of AI in oncology. The literature to date has dealt extensively with radiomics, genomics, pathology, risk stratification, lesion detection, and therapy response. Current hot topics identified by our analysis highlight the potential application of AI in radiomics and precision oncology.

Wu T ，Duan Y ，Zhang T ，Tian W ，Liu H ，Deng Y ... -  《-》

Mapping the research of mitochondria and Parkinson's disease: a bibliometric analysis.

Parkinson's disease (PD) is a chronic, progressive neurodegenerative disorder primarily affecting the elderly. Relevant studies suggest a significant connection between the mitochondria and PD. Publications exploring this connection have steadily increased in recent years. This study employs a bibliometric approach to comprehensively analyze the current status and future directions of the research on mitochondria and PD. We retrieved data from the Web of Science database and used CiteSpace, VOSviewer, and "Bibliometrix" software to visually analyze various aspects of the research field. These aspects included the number of published papers, contributing countries and institutions, authors, publishing journals, cited references, and keywords. Our analysis identified a total of 3,291 publications involving 14,670 authors from 2,836 organizations across 78 countries. The publication volume exhibited a continuous upward trend from 1999 to 2023. The United States emerged as the leading force in this research area, contributing the highest number of high-quality publications. Notably, the United States collaborated extensively with Germany and the United Kingdom. The University of Pittsburgh stood out as the most prolific institution. Harvard University had the highest academic influence and closely cooperated with the University of Pittsburgh, Juntendo University, and McGill University. Dr. Hattori Nobutaka was identified as the most prolific author, while Dr. Youle, Richard J emerged as the most influential author based on the highest average citation frequency. The Journal of Neurochemistry was the most published journal. The most co-cited paper was titled "Hereditary early-onset Parkinson's disease caused by mutations in PINK1." The major keywords included oxidative stress, alpha-synuclein, pink1, mitophagy, and mitochondrial dysfunction. Mitofusin 2, ubiquitin, and mitochondrial quality control have been identified as new research hotspots in recent years. Mitochondria-PD research is experiencing a steady increase in activity, fueled by increasing close collaboration between countries and different institutions. However, there is a need to further strengthen collaboration and communication between developed and developing nations. Current research has focused on the specific mechanisms of mitochondrial dysfunction and their relationship with PD. Mitofusin 2, ubiquitin, and mitochondrial quality control are positioned to be the hotspots and future research directions.

Chen YJ ，Xie MR ，Zhou SQ ，Liu F ... -  《Frontiers in Neurology》

Knowledge mapping of neonatal electroencephalogram: A bibliometric analysis (2004-2022).

Electroencephalography (EEG), a widely used noninvasive neurophysiological diagnostic tool, has experienced substantial advancements from 2004 to 2022, particularly in neonatal applications. Utilizing a bibliometric methodology, this study delineates the knowledge structure and identifies emergent trends within neonatal EEG research. An exhaustive literature search was conducted on the Web of Science Core Collection (WoSCC) database to identify publications related to neonatal EEG from 2004 to 2022. Analytical tools such as VOSviewer, CiteSpace, and the R package "bibliometrix" were employed to facilitate this investigation. The search yielded 2501 articles originating from 79 countries, with the United States and England being the predominant contributors. A yearly upward trend in publications concerning neonatal EEG was observed. Notable research institutions leading this field include the University of Helsinki, University College London, and University College Cork. Clinical Neurophysiology is identified as the foremost journal in this realm, with Pediatrics as the most frequently co-cited journal. The collective body of work from 9977 authors highlights Sampsa Vanhatalo as the most prolific contributor, while Mark Steven Scher is recognized as the most frequently co-cited author. Key terms such as "seizures," "epilepsy," "hypoxic-ischemic encephalopathy," "amplitude-integrated EEG," and "brain injury" represent the focal research themes. This bibliometric analysis offers the first comprehensive review, encapsulating research trends and progress in neonatal EEG. It reveals current research frontiers and crucial directions, providing an essential resource for researchers engaged in neonatal neuroscience.

Zhang R ，Shi L ，Zhang L ，Lin X ，Bao Y ，Jiang F ，Wu C ，Wang J ... -  《Brain and Behavior》

Trends and hotspots on the relationship between gut microbiota and Parkinson's Disease: a bibliometric analysis.

Parkinson's disease (PD) is a neurodegenerative disorder that significantly impacts patients' quality of life. Recent evidence has highlighted a complex relationship between the gut microbiota (GM) and PD. Understanding this relationship is crucial for potentially targeting GM in PD treatment and expanding therapeutic options. This study aimed to comprehensively analyze the global landscape, trends, and research focus on GM and PD using bibliometric analysis. Utilizing publications from the Web of Science Core Collection (WsSCC), bibliometric tools such as the R package 'Bibliometrix,' VOS viewer, and CiteSpace software were employed to assess parameters like yearly publications, countries/regions, institutions, and authors. Research trends and hotspots were identified through keyword analysis. The results revealed 1,161 articles published between 2013-2023, with China leading in publications (n=352, 30.31% of total), while the United States had a higher influence (H-index=58). The University of California System was the top institution in terms of publications (n=35), with the National Natural Science Foundation of China funding the most projects (n=172). Keshavarzian A and Sampson TR were the authors with the highest publication and co-citation counts, respectively. The International Journal of Molecular Sciences had the most articles published (n=48). Keyword analysis identified parkinson's disease, gut microbiota, short-chain fatty acids, inflammation, and probiotics as main research topics. Biomarkers, ketogenic diet, and NF-κB were recent research hotspots and trends (2021-2023). The current study conducts an objective and comprehensive analysis of these publications, identifying trends and hotspots in the field of research. The findings offer valuable insights to scholars globally and in-vestigate potential therapeutic strategies for Parkinson's Disease.

Li X ，Hao X ，Chen C ，Zhai C ，Pan T ，Zhou X ，Liu Y ，Wu D ，Chen X ... -  《Frontiers in Cellular and Infection Microbiology》