Bibliometric and visualized analysis of ocular drug delivery from 2001 to 2020.
To perform a bibliometric analysis in the field of ocular drug delivery research to characterize the current international trends and to present visual representations of the past and emerging trends on ocular drug delivery research over the past decade.
In this cross-sectional study, a bibliometric analysis of data retrieved and extracted from the Web of Science Core Collection (WoSCC) database was performed to analyze evolution and theme trends on ocular drug delivery research from January 1, 2001, to December 31, 2020. A total of 4334 articles on ocular drug delivery were evaluated for specific characteristics, such as publication year, journals, authors, institutions, countries/regions, references, and keywords. Co-authorship analysis, co-occurrence analysis, co-citation analysis, and network visualization were constructed by VOSviewer. Some important subtopics identified by bibliometric characterization were further discussed and reviewed.
From 2001 to 2020, the annual global publications increased by 746.15%, from 52 to 440. International Journal of Pharmaceutics published the most manuscripts (250 publications) and produced the highest citations (9509 citations), followed by Investigative Ophthalmology & Visual Science (202 publications) and Journal of Ocular Pharmacology and Therapeutics (136 publications). The United States (1289 publications, 31,512 citations), the University of Florida (82 publications, 2986 citations), and Chauhan, Anuj (52 publications, 2354 citations) were the most productive and impactful institution, country, and author respectively. The co-occurrence cluster analysis of the top 100 keywords form five clusters: (1) micro/nano ocular drug delivery systems; (2) the treatment of inflammation and posterior diseases; (3) macroscopic ocular drug delivery systems/devices; (4) the characteristics of drug delivery systems; (5) and the ocular drug delivery for glaucoma treatment. Diabetic macular edema, anti-VEGF, ranibizumab, bevacizumab, micelles and latanoprost, were the latest high-frequency keywords, indicating the emerging frontiers of ocular drug delivery. Further discussions into the subtopics were provided to assist researchers to determine the range of research topics and plan research direction.
Over the last two decades there has been a progressive increase in the number of publications and citations on research related to ocular drug delivery across many countries, institutions, and authors. The present study sheds light on current trends, global collaboration patterns, basic knowledge, research hotspots, and emerging frontiers of ocular drug delivery. Novel solutions for ocular drug delivery and the treatment of inflammation and posterior diseases were the major themes over the last 20 years.
Peng C
，Kuang L
，Zhao J
，Ross AE
，Wang Z
，Ciolino JB
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A bibliometric analysis and visualization of photothermal therapy on cancer.
Cancer is one of the most lethal diseases in the world, and photothermal therapy was reported recently as a new and effective therapy for cancer. This study offers the bibliometric and visualization analysis of photothermal therapy on cancer.
A record of 6,233 papers in this field from 1995 to 2019 was obtained based on the Web of Science Core Collection (WoSCC). And CiteSpace was used to analyze the annual trends of publications, countries, institutions, journals, co-cited references, and keywords in the field of photothermal therapy on cancer.
We identified that the number of publications continually increased over the time. The most productive country and institution in this field was China and Chinese Academy of Sciences, respectively. The ACS Appl Mater Interfaces was the most active journal. Co-cited references analysis revealed the top landmark articles in the field. Co-occurrence keywords and their clustered network were analyzed, revealing that materials, especially nanomaterials, used in photothermal therapy, remained the hotspots in this research field. Timezone view and burst detection of keywords showed that nanomaterials were always the hotspots and the frontier topics in this field.
The current study revealed that photothermal therapy has become a subject of growing study and a very important research area. In addition, the research of materials in photothermal therapy, especially nanomaterials, which were applied in photothermal therapy to treat cancer effectively, is the foci and the frontier topic in this field.
Wang X
，Li D
，Huang X
，Luo Q
，Li X
，Zhang X
，Zhang L
... -
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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
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ResearchGate
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钛学术
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