METHODS: A comprehensive search was conducted in the Web of Science (WOS) electronic database to identify the top 100 most-cited articles on AI in orthodontics and orthognathic surgery. Publication and citation data were obtained and further analyzed and visualized using R Biblioshiny. The key domains of the 100 articles were also identified.
RESULTS: The top 100 most-cited articles were published between 2005 and 2022, contributed by 458 authors, with an average citation count of 22.09. South Korea emerged as the leading contributor with the highest number of publications (28) and citations (595), followed by China (16, 373), and the United States (7, 248). Notably, six South Korean authors ranked among the top 10 contributors, and three South Korean institutions were listed as the most productive. International collaborations were predominantly observed between the United States, China, and South Korea. The main domains of the articles focused on automated imaging assessment (42%), aiding diagnosis and treatment planning (34%), and the assessment of growth and development (10%). Besides, a positive correlation was observed between the testing sample size and citation counts (P = 0.010), as well as between the time of publication and citation counts (P
METHODS: To understand the research status of schistosomiasis and toxoplasmosis in China, academic articles published in Chinese journals from 1980 to 2021 were retrieved from China National Knowledge Infrastructure (CNKI) and Wanfang databases. The Bibliographic Items Co-occurrence Matrix Builder (BICOMB) software was used to extract and analyze the keyword frequencies. The 'K/A ratio' as the frequency of a keyword that occurred in all the articles within a certain time stage was calculated to compare the popularity of the same keyword in different time stages. Keyword co-occurrence network maps were constructed by VOSviewer software.
RESULTS: A total of 18,508 articles in the research field of Schistosoma and 13,289 articles in the field of Toxoplasma gondii were included. Results in both fields showed some similarities: the annual number of articles presented an increasing trend before entering the 21st century and decreased rapidly in recent years. Two opposite changing trends of keyword frequency could be observed in the K/A ratio analysis: the K/A ratios of 'Surveillance' and 'Infection' continuously increased over time, while those of 'Schistosoma mansoni' and 'Mesenteric lymph nodes' decreased. The diversification of keyword co-occurrence networks could be observed in the co-occurrence network maps.
CONCLUSIONS: This bibliometric analysis reveals trends in research themes in the fields of Schistosoma and Toxoplasma gondii from 1980 to 2021, presenting China's experience such as a high degree of government involvement and multidisciplinary participation in schistosomiasis and toxoplasmosis control and elimination.
OBJECTIVE: This paper aims to introduce a GAN technology for the diagnosis of eye disorders, particularly glaucoma. This paper illustrates deep adversarial learning as a potential diagnostic tool and the challenges involved in its implementation. This study describes and analyzes many of the pitfalls and problems that researchers will need to overcome to implement this kind of technology.
METHODS: To organize this review comprehensively, articles and reviews were collected using the following keywords: ("Glaucoma," "optic disc," "blood vessels") and ("receptive field," "loss function," "GAN," "Generative Adversarial Network," "Deep learning," "CNN," "convolutional neural network" OR encoder). The records were identified from 5 highly reputed databases: IEEE Xplore, Web of Science, Scopus, ScienceDirect, and PubMed. These libraries broadly cover the technical and medical literature. Publications within the last 5 years, specifically 2015-2020, were included because the target GAN technique was invented only in 2014 and the publishing date of the collected papers was not earlier than 2016. Duplicate records were removed, and irrelevant titles and abstracts were excluded. In addition, we excluded papers that used optical coherence tomography and visual field images, except for those with 2D images. A large-scale systematic analysis was performed, and then a summarized taxonomy was generated. Furthermore, the results of the collected articles were summarized and a visual representation of the results was presented on a T-shaped matrix diagram. This study was conducted between March 2020 and November 2020.
RESULTS: We found 59 articles after conducting a comprehensive survey of the literature. Among the 59 articles, 30 present actual attempts to synthesize images and provide accurate segmentation/classification using single/multiple landmarks or share certain experiences. The other 29 articles discuss the recent advances in GANs, do practical experiments, and contain analytical studies of retinal disease.
CONCLUSIONS: Recent deep learning techniques, namely GANs, have shown encouraging performance in retinal disease detection. Although this methodology involves an extensive computing budget and optimization process, it saturates the greedy nature of deep learning techniques by synthesizing images and solves major medical issues. This paper contributes to this research field by offering a thorough analysis of existing works, highlighting current limitations, and suggesting alternatives to support other researchers and participants in further improving and strengthening future work. Finally, new directions for this research have been identified.
METHODS: The methodology was based on the search process described in the paper, "Bibliography of clinical research in Malaysia: methods and brief results". The search databases included PubMed, Scopus and several Malaysian journals such as MyJurnal and UKM Journal Repository, by using the following keywords: (heart valve disease OR infective endocarditis OR rheumatic heart disease) and (Malaysia).
RESULTS: In all 94 papers were identified of which 39 papers were selected and reviewed on the basis of their relevance. The local studies contributed to the knowledge and understanding of the epidemiology, aetiology, pathophysiology, clinical presentations, investigations, treatment, and outcomes of heart valve disease in the country.
DISCUSSION: The clinical relevance of the studies performed in the country is discussed along with recommendations for future research.
Methods: We searched PubMed-MEDLINE, Embase and Scopus, from inception to 20 Sep 2019, and reviewed major conferences' abstracts, for randomised controlled trials of ICI in advanced-stage NSCLC (Stage IIIB or IV) without EGFR mutation that reported hazard ratios (HRs) stratified by geographical region including the region "Asia" or "East Asia". The primary outcome measures were overall survival (OS) and progression-free survival (PFS). The pooled HR and its 95% confidence interval (CI) for OS and PFS in East Asians and non-East Asians were calculated using a random effect model and the difference compared using an interaction test.
Results: A total of 5,465 patients from 7 randomised controlled trials involving CTLA-4 and/or PD-1/L1 inhibitors were included, with 1,740 (32%) East Asians and 3,725 (68%) non-East Asians. ICI was associated with an improvement in OS and PFS for both East Asian (OS HR, 0.74; 95% CI, 0.65-0.85; PFS HR, 0.56; 95% CI, 0.40-0.79) and non-East Asian patients (OS HR, 0.78; 95% CI, 0.72-0.85; PFS HR, 0.69; 95% CI, 0.56-0.85), with no significant difference between the two groups (Pinteraction=0.55 for OS; Pinteraction=0.33 for PFS). Subgroup analyses showed a statistically significant superior PFS (but not OS) for East Asians than non-East Asians in trials that used immune checkpoint inhibitor in the first-line treatment (Pinteraction=0.02). No significant regional difference was found in further subgroups of pure ICI and combination of ICI with chemotherapy.
Conclusions: There is no significant difference in response to ICI between East Asians and non-East Asians with advanced stage NSCLC, and the statistically significant subgroup difference in PFS in the first line use of ICI may not be clinically significant.
METHODOLOGY: The Clarivate Analytics' Web of Science 'All Databases' was used to search and analyse the 100 most frequently cited randomized controlled trials, systematic reviews and meta-analyses having 'randomized', 'randomised', 'randomized controlled', 'randomised controlled', 'randomized controlled trial', 'randomized controlled trials', 'clinical trial', 'systematic', 'systematic review', 'meta-analysis', and 'meta-analyses' in the title section. The 'International Endodontic Journal', 'Journal of Endodontics', 'Oral Surgery Oral Medicine Oral Pathology Oral Radiology and Endodontology', 'Australian Endodontic Journal', 'Endodontics & Dental Traumatology', 'Endo-Endodontic Practice Today' and 'European Endodontic Journal' were included in the publication name section. After ranking the articles in a descending order based on their citation counts, each article was cross-matched with the citation counts in Elsevier's Scopus and Google Scholar. The articles were analysed, and information on citation counts, citation density, year of publication, contributing authors, institutions and countries, journal of publication, study design, topic of the article and keywords was extracted.
RESULTS: The citation counts of the 100 most-cited articles varied from 235 to 20 (Web of Science), 276 to 17 (Scopus) and 696 to 1 (Google Scholar). The year in which the top 100 articles were published was 2010 (n = 13). Among 373 authors, the greatest number of articles was associated with three individuals namely Reader A (n = 5), Beck M (n = 5) and Kvist T (n = 5). Most of the articles originated from the United States (n = 24) with the greatest contribution from Ohio State University (USA) (n = 5). Randomized controlled trials were the most frequent study design (n = 45) followed by systematic reviews (n = 30) with outcome studies of root canal treatment being the major topic (n = 35). The Journal of Endodontics published the largest number of included articles (n = 70) followed by the International Endodontic Journal (n = 27). Among 259 unique keywords, meta-analysis (n = 23) and systematic review (n = 23) were the most frequently used.
CONCLUSION: This study has revealed that year of publication had no obvious impact on citation count. The bibliometric analysis highlighted the quantity and quality of research, and the evolution of scientific advancements made in the field of Endodontology over time. Articles before 1996, that is prior to the CONSORT statement that encouraged authors to include specific terms in the title and keywords, may not have been included in this electronic search.