Altmetric Analysis of Artificial Intelligence Articles in Plastic Surgery.
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ABSTRACT:
SUBMITTER: Bogdanovich B
PROVIDER: S-EPMC11001444 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
Publications
Altmetric Analysis of Artificial Intelligence Articles in Plastic Surgery.
Bogdanovich Brennan B Shah Pearl P Patel Parth A PA Bui Tommy T Boyd Carter J CJ
Archives of plastic surgery 20240129 2
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Project description:BackgroundRecent years have witnessed an explosive surge in dental research related to artificial intelligence (AI). These applications have optimised dental workflows, demonstrating significant clinical importance. Understanding the current landscape and trends of this topic is crucial for both clinicians and researchers to utilise and advance this technology. However, a comprehensive scientometric study regarding this field had yet to be performed.MethodsA literature search was conducted in the Web of Science Core Collection database to identify eligible "research articles" and "reviews." Literature screening and exclusion were performed by 2 investigators. Thereafter, VOSviewer was utilised in co-occurrence analysis and CiteSpace in co-citation analysis. R package Bibliometrix was employed to automatically calculate scientific impacts, determining the core authors and journals. Altmetric data were described narratively and supplemented with Spearman correlation analysis.ResultsA total of 1558 research publications were included. During the past 5 years, AI-related dental publications drastically increased in number, from 36 to 581. Diagnostics and Scientific Reports published the most articles, whereas Journal of Dental Research received the highest number of citations per article. China, the US, and South Korea emerged as the most prolific countries, whilst Germany received the highest number of citations per article (23.29). Charité Universitätsmedizin Berlin was the institution with the highest number of publications and citations per article (29.16). Altmetric Attention Score was correlated with News Mentions (P < .001), and significant associations were observed amongst Dimension Citations, Mendeley Readers, and Web of Science Citations (P < .001).ConclusionsThe publication numbers regarding AI-related dental research have been rising rapidly and may continue their upwards trend. China, the US, South Korea, and Germany had promoted the progress of AI-related dental research. Disease diagnosis, orthodontic applications, and morphology segmentation were current hotspots. Attention mechanism, explainable AI, multimodal data fusion, and AI-generated text assistants necessitate future research and exploration.
| S-EPMC11806303 | biostudies-literature
Project description:BackgroundThe application of artificial intelligence (AI) in orthodontics and orthognathic surgery has gained significant attention in recent years. However, there is a lack of bibliometric reports that analyze the academic literature in this field to identify publishing and citation trends. By conducting an analysis of the top 100 most-cited articles on AI in orthodontics and orthognathic surgery, we aim to unveil popular research topics, key authors, institutions, countries, and journals in this area.MethodsA 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.ResultsThe 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 < 0.001).ConclusionsThe utilization of AI in orthodontics and orthognathic surgery has shown remarkable progress, particularly in the domains of imaging analysis, diagnosis and treatment planning, and growth and development assessment. This bibliometric analysis provides valuable insights into the top-cited articles and the trends of AI research in this field.
| S-EPMC10463886 | biostudies-literature
Project description:BackgroundArtificial intelligence (AI) is emerging as a transformative technology with potential applications in various plastic surgery procedures and plastic surgery education. This article examines the views of plastic surgeons and residents on the role of AI in the field of plastic surgery.MethodsA 34-question survey on AI's role in plastic surgery was distributed to 564 plastic surgeons worldwide, and we received responses from 153 (26.77%) with the majority from Latin America. The survey explored various aspects such as current AI experience, attitudes toward AI, data sources, ethical considerations, and future prospects of AI in plastic surgery and education. Predictions from AI using ChatGPT for each question were compared with the actual survey responses.ResultsThe study found that most participants had little or no prior AI experience. Although some believed AI could enhance accuracy and visualization, opinions on its impact on surgical time, patient recovery, and satisfaction were mixed. Concerns included patient privacy, data security, costs, and informed consent. Valuable AI training data sources were identified, and there was agreement on the importance of standards and transparency. Respondents expected AI's increasing role in reconstructive and aesthetic surgery, suggesting its integration into residency programs, addressing administrative challenges, and patient complications. Confidence in the enduring importance of human professionals was expressed, with interest in further AI research.ConclusionThe survey's findings underscore the need to harness AI's potential while preserving human professionals' roles through informed consent, standardization, and AI education in plastic surgery.
| S-EPMC10781127 | biostudies-literature
Project description:Social media has become a valuable tool for the distribution of scientific content. This investigation examined the most mentioned articles in orthopaedics and identified factors concurrent with greater dissemination. Altmetric Attention Score (AAS), which measures the online attention of an article, was examined for 88,683 publications in the top 50 orthopaedic journals by 2021 impact factor. Comparative and correlational analyses were completed. Overall, average AAS and citation count of the 100 most mentioned articles were 606.7 (SD ± 272.0) and 67.55 (SD ± 98.01), respectively. These articles had primarily male first authors (75%), were produced predominantly in the United States (60%), concerned the subspecialty of sports medicine (28%), and were cross-sectional analyses (22%). There were significant differences in AAS between publications (p < 0.05) by the degree of collaboration and the type of article. Such insights can guide authors when considering avenues to increase the impact of their research.
| S-EPMC10432777 | biostudies-literature
Project description:IntroductionCitation counts of articles have been used to measure scientific outcomes and assess suitability for grant applications. However, citation counts are not without limitations. With the rise of social media, altmetric scores may provide an alternative assessment tool.ObjectivesThe aims of the study were to assess the characteristics of highly cited articles in medical professionalism and their altmetric scores.MethodsThe Web of Science was searched for top-cited articles in medical professionalism, and the characteristics of each article were identified. The altmetric database was searched to identify report for each identified article. A model to assess the relationship between the number of citations and each of the key characteristics as well as altmetric scores was developed.ResultsNo correlations were found between the number of citations and number of years since publication (p=0.192), number of institutes (p=0.081), number of authors (p=0.270), females in authorship (p=0.150) or number of grants (p=0.384). The altmetric scores varied from 0 to 155, total=806, median=5.0, (IQR=20). Twitter (54%) and Mendeley (62%) were the most popular altmetric resources. No correlation was found between the number of citations and the altmetric scores (p=0.661). However, a correlation was found for articles published in 2007 and after (n=17, p=0.023). To further assess these variables, a model was developed using multivariate analysis; did not show significant differences across subgroups. The topics covered were learning and teaching professionalism, curriculum issues, professional and unprofessional behaviour.ConclusionsAltmetric scores of articles were significantly correlated with citations counts for articles published in 2007 and after. Highly cited articles were produced mainly by the USA, Canada and the UK. The study reflects the emerging role of social media in research dissemination. Future studies should investigate the specific features of highly cited articles and factors reinforcing distribution of research data among scholars and non-scholars.
| S-EPMC6677941 | biostudies-literature
Project description:Artificial intelligence (AI) transforms medical images into high-throughput mineable data. Machine learning algorithms, which can be designed for modeling for lesion detection, target segmentation, disease diagnosis, and prognosis prediction, have markedly promoted precision medicine for clinical decision support. There has been a dramatic increase in the number of articles, including articles on ultrasound with AI, published in only a few years. Given the unique properties of ultrasound that differentiate it from other imaging modalities, including real-time scanning, operator-dependence, and multi-modality, readers should pay additional attention to assessing studies that rely on ultrasound AI. This review offers the readers a targeted guide covering critical points that can be used to identify strong and underpowered ultrasound AI studies.
| S-EPMC8222674 | biostudies-literature
Project description:In this bibliometric analysis, the authors analyze the top 100 (T100) most cited articles on cosmetic upper facial plastic surgery. Throughout this study, the objective of the authors is to delineate the trends in cosmetic upper facial surgeries to identify prevailing techniques, emerging trends, and potential areas of future investigation. The articles were indexed from the Web of Science database and were extracted in a double-blinded manner by 2 independent graders. The search phrase used covered a wide range of cosmetic upper facial plastic surgeries, of which a short sample is included: ("cosmetic*" AND "bleph*") OR ("cosmetic*" AND "upper eyelid blepharoplasty") OR ("cosmetic*" AND "lower eyelid blepharoplasty"). In their statistical analysis of the number of citations received in each article in the T100, the authors reveal an average of 55.1 citations (a standard deviation of 38.7). Surgical methods were the most commonly cited unique study area, with 30% of the T100, followed by botulinum toxin and complication management with 29% and 15% of the T100, respectively. The unique study area with the highest average citations received was botulinum toxin, with an average of 64.7 citations. Invasive procedures made up 55% of the T100 articles. The authors found that the late 1990s and 2000s were a burgeoning period of growth in this field and highlight the evolution of many contemporary popular cosmetic procedures over time. Particularly, a growth in minimally invasive procedures was noted, with noted impacts in aesthetics training and research focus.Level of evidence 4 therapeutic
| S-EPMC11758881 | biostudies-literature
Project description:ObjectiveThis study examines the extent to which retracted articles pertaining to COVID-19 have been shared via social and mass media based on altmetric scores.MethodsSeventy-one retracted articles related to COVID-19 were identified from relevant databases, of which thirty-nine had an Altmetric Attention Score obtained using the Altmetrics Bookmarklet. Data extracted from the articles include overall attention score and demographics of sharers (e.g., geographic location, professional affiliation).ResultsRetracted articles related to COVID-19 were shared tens of thousands of times to an audience of potentially hundreds of millions of readers and followers. Twitter was the largest medium for sharing these articles, and the United States was the country with the most sharers. While general members of the public were the largest proportion of sharers, researchers and professionals were not immune to sharing these articles on social media and on websites, blogs, or news media.ConclusionsThese findings have potential implications for better understanding the spread of misleading or false information perpetuated in retracted scholarly publications. They emphasize the importance of quality peer review and research ethics among journals and responsibility among individuals who wish to share research findings.
| S-EPMC8830369 | biostudies-literature
Project description:ObjectiveThis study aimed to identify the 100 top-cited articles on dentin adhesives utilizing comprehensive bibliometric and altmetric analyses.Materials and methodsThe Institute of Scientific Information Web of Knowledge database was used to compile the top-cited articles published from 1945 through February 12, 2023. Citation counts were manually retrieved for each article from Scopus, Google Scholar, Dimensions, and Altmetric. The articles were analyzed in terms of their number of citations, year, journal name, author (name, institution, and country), and type and specific field of study. We used descriptive statistics to summarize the results.ResultsThe analysis revealed that the top 100 cited articles originated from 18 English-language journals and collectively accumulated a remarkable 34526 citations. The article with the highest number of citations garnered 1288 references. Among authors, Van Meerbeek B. stood out with nine articles and 4650 citations, followed by Pashley D.H. with six articles and 2769 citations. Japan was the leading contributor by country, while the Catholic University of Leuven led in terms of institutions with 20 articles.ConclusionAccording to this study, basic research and review articles garnered the most citations, respectively. The citation analysis revealed different trends for researchers, the first being that researchers have focused on basic fields such as the ultramorphology of dentin and adhesive interfaces, followed by bond strength to dentin. Two studies on clinical experiences suggested that studies with high-level evidence, such as systematic reviews, meta-analyses, or randomized controlled clinical trials, are required.Clinical relevanceIt is identified that more studies with high-level evidence-based research are needed in the field of dental adhesives.
| S-EPMC10787682 | biostudies-literature
Project description:The number of retracted articles has grown fast. However, the extent to which researchers and the public are made adequately aware of these retractions and how the media and social media respond to them remains unknown. Here, we aimed to evaluate the media and social media attention received by retracted articles and assess also the attention they receive post-retraction versus pre-retraction. We downloaded all records of retracted literature maintained by the Retraction Watch Database and originally published between January 1, 2010 to December 31, 2015. For all 3,008 retracted articles with a separate DOI for the original and its retraction, we downloaded the respective Altmetric Attention Score (AAS) (from Altmetric) and citation count (from Crossref), for the original article and its retraction notice on June 6, 2018. We also compared the AAS of a random sample of 572 retracted full journal articles available on PubMed to that of unretracted full articles matched from the same issue and journal. 1,687 (56.1%) of retracted research articles received some amount of Altmetric attention, and 165 (5.5%) were even considered popular (AAS>20). 31 (1.0%) of 2,953 with a record on Crossref received >100 citations by June 6, 2018. Popular articles received substantially more attention than their retraction, even after adjusting for attention received post-retraction (Median difference, 29; 95% CI, 17-61). Unreliable results were the most frequent reason for retraction of popular articles (32; 19%), while fake peer review was the most common reason (421; 15%) for the retraction of other articles. In comparison to matched articles, retracted articles tended to receive more Altmetric attention (23/31 matched groups; P-value, 0.01), even after adjusting for attention received post-retraction. Our findings reveal that retracted articles may receive high attention from media and social media and that for popular articles, pre-retraction attention far outweighs post-retraction attention.
| S-EPMC8115781 | biostudies-literature