Background Interdisciplinary research is an important feature of precision medicine. However, the accurate cross-disciplinary status of precision medicine is still unclear. Objective The aim of this study is to present the nature of interdisciplinary collaboration in precision medicine based on co-occurrences and social network analysis. Methods A total of 7544 studies about precision medicine, published between 2010 and 2019, were collected from the Web of Science database. We analyzed interdisciplinarity with descriptive statistics, co-occurrence analysis, and social network analysis. An evolutionary graph and strategic diagram were created to clarify the development of streams and trends in disciplinary communities. Results The results indicate that 105 disciplines are involved in precision medicine research and cover a wide range. However, the disciplinary distribution is unbalanced. Current cross-disciplinary collaboration in precision medicine mainly focuses on clinical application and technology-associated disciplines. The characteristics of the disciplinary collaboration network are as follows: (1) disciplinary cooperation in precision medicine is not mature or centralized; (2) the leading disciplines are absent; (3) the pattern of disciplinary cooperation is mostly indirect rather than direct. There are 7 interdisciplinary communities in the precision medicine collaboration network; however, their positions in the network differ. Community 4, with disciplines such as genetics and heredity in the core position, is the most central and cooperative discipline in the interdisciplinary network. This indicates that Community 4 represents a relatively mature direction in interdisciplinary cooperation in precision medicine. Finally, according to the evolution graph, we clearly present the development streams of disciplinary collaborations in precision medicine. We describe the scale and the time frame for development trends and distributions in detail. Importantly, we use evolution graphs to accurately estimate the developmental trend of precision medicine, such as biological big data processing, molecular imaging, and widespread clinical applications. Conclusions This study can help researchers, clinicians, and policymakers comprehensively understand the overall network of interdisciplinary cooperation in precision medicine. More importantly, we quantitatively and precisely present the history of interdisciplinary cooperation and accurately predict the developing trends of interdisciplinary cooperation in precision medicine.
INTRODUCTION Smoking cessation is an efficient approach to reducing disease burden. Traditional Chinese Medicine (TCM) therapies such as acupuncture, acupressure, and herbal drugs are often used to help quit smoking. However, there is a lack of overarching bibliometric analysis of the clinical research on smoking cessation focusing on TCM. The aim of our study is to explore the current patterns and trends of TCM therapy for smoking cessation through bibliometric methods with visual presentation. METHODS This study is an assessment of academic publications retrieved from the Scopus database on smoking cessation using TCM therapy published in the period 2005-2021. Sankey diagram, word-cloud, network analysis, thematic maps, treemaps, and the collaborative work of authors, institutions and countries, were used to identify research trends on TCM therapy for smoking cessation. The total cited index and H-index (for journals, authors, countries, organizations) were used to identify the trends of worldwide development by R Package and Excel 2016. RESULTS There was an upward trend, with some fluctuations, of 1908 articles from 2005 to 2021. The most productive country was China. The top institution in this field was Beijing University. The dominant author that contributed to TCM therapy for smoking cessation was Wang Y, who has the highest H-Index. The most productive cited journals were Evidence-Based Complementary and Alternative Medicines and the Chinese Journal of Clinical Rehabilitation. Liu L, (2011, STROKE) had the highest centrality. The keywords 'acupuncture', 'traditional Chinese medicine', 'colitis', 'hypertension', 'chronic obstructive pulmonary disease', 'risk factors' and 'alternative medicine' ranked highest in frequency. The diseases of healthy people concerned mainly cardiovascular, cancer, diabetes, hypertension and pregnancy. The diseases of the patients concerned mainly cancer, diabetes, hematopathy, stroke, cardiovascular, diabetes, lung disease, and hypertension. Treatment methods were mainly traditional Chinese medicine and acupuncture. The research methods mainly included randomized controlled trials that were multi-center and double-blind. CONCLUSIONS A substantial number of articles on TCM therapy for smoking cessation, mainly focusing on TCM and acupuncture were identified. It is worth noting that research that focused on TCM therapy for smoking cessation also was related to COVID-19.
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