The 100 most influential articles in myopia: a bibliometric analysis

AIM: To identify and characterize the 100 most influential articles in the field of myopia over the last decades. METHODS: Articles on myopia published between January 1975 and March 2020 were searched through the Web of Science Core Collection database. Two independent authors reviewed and determined the 100 most cited articles. The characteristics of each eligible article were recorded, including authors, institutions, countries, journals, publication date, total citations (TCs), annual citations (ACs), research focus and article type. RESULTS: The top 100 most influential articles were published between 1983 and 2016, with 1999 as the most prolific year. The mean number of TCs was 288 (range: 193-537) and the mean number of ACs was 19 (range: 7-109). Treatment and epidemiology of myopia were the most important research focus. These articles were published in 21 journals led by Ophthalmology (29%) followed by Investigative Ophthalmology & Visual Science (23%). The number of ACs for articles published in the last ten years was significantly higher than that for the other most-cited articles (44 vs 16, Mann-Whitney U test P<0.01). There is no difference in the number of TCs between original articles and review articles, while the number of ACs for review articles was significantly higher than that for original articles (22 vs 17, Mann-Whitney U test P<0.05). CONCLUSION: This bibliometric analysis can provide us with concise information about the development trend of research in the field of myopia in the past few decades, and provide an important reference for researchers to guide future research.

Mapping research trends of uveal melanoma: a bibliometric analysis

Background To explore the research trends for uveal melanoma with bibliometric methods using Web of Science Core Collection (WoSCC) and PubMed (PM). Methods To find UM-related studies, “uveal melanoma” was used as search term in the WoSCC and PM for the period time from 2000 to 2020. Bibliographic coupling analysis was used to investigate the journals with the highest number of UM-related publications. VOSviewer (VV) was used for mapping the knowledge domain and visualizing the co-occurrence of terms, authors, organizations, countries, co-citation literature, and keywords. The knowledge map based on WoSCC and PM was compared. Results In the WoSCC 3,748 articles were found, while in PM the search resulted in 3,403 articles. The number of original articles has steadily grown in general in the past two decades. The top ten authors were contributing to 23% (n = 856) of all publications, while the top 10 institutions published 41% (n = 1524) of all articles. The top 3 journals with the highest number of publications for UM-related research included Investigative ophthalmology & visual science, Ophthalmology, and British Journal of Ophthalmology. Co-occurrence analysis based on author keywords showed 6 clusters. The most frequent keywords included are metastasis, prognosis, and brachytherapy. The latest research hotspots focused on BAP1, immunotherapy and GNAQ. Conclusions Genetics and immunology are the latest research frontiers in uveal melanoma. There is a clear need for interdisciplinary, molecular and clinical research approaches to improve the fatal prognosis of uveal melanoma patients.

The application of Artificial Intelligence to Ophthalmology: A bibliometric study (2000-2021)

Background. Artificial Intelligence (AI) is an advanced technology for the latest 20 years. Machine learning (ML) and deep learning (DL) are the major innovations for AI, which has been applied for multiple fields. Ophthalmology has become to be one of the most significant disciplines for human healthcare. Methodology. This study utilizes methods of text mining and bibliometric analysis to explore applications of AI to ophthalmology. 179 related articles from Web of Science (WOS) and 96 papers from China National Knowledge Infrastructure (CNKI) are explored during the period of 2000 to 2021. A descriptive analysis of major trends, journal releasing, topic mapping and quotation relationships is implemented in this paper. Leading authors, journals, institutions, nations and references in the related research are identified. Results. Findings show that the application of AI technologies in ophthalmologic diagnosis with optical coherence tomography (OCT) fundus images is the core topic for this area’s studies, especially for diabetic retinopathy (DR), aged macular degeneration (AMD) and glaucoma. It is also be predicted as the core direction over the recent years. Besides, The USA, England and China is the most competitive countries in this scientific filed. Journals of Ophthalmology, Investigative Ophthalmology and Visual Science, Eye, Acta Ophthalmologica and Scientific Reports are the top five journal related to the research area. There is a significant difference between WOS and CNKI databases pertaining to the application of Artificial Intelligence (AI) to ophthalmology, especially for the historic development, topic mapping and discipline category. Finally, the potential academic value of interdisciplinary subject of “AI in Ophthalmology” and tradition Chinese medicine (TRM) is discussed. Limitations and suggestions for the future research is indicated at the end of this paper.

HOW TO USE THE VISUAL IN SCIENTIFIC STUDIES? (FOLLOWING PETER GALISON AND LORRAINE DASTON)

В отличие от визуального как компонента научных практик, исследование научных визуализаций – достаточно молодая, совсем недавно начавшая набирать обороты область эпистемологии. Несмотря на свой «юный» возраст, данная сфера исследований уже успела обогатиться разного рода подходами, концептами и самостоятельными выводами. На наш взгляд, книгу Питера Галисона и Лоррейн Дастон «Объективность» можно рассматривать в качестве труда, который и привносит очевидные новшества в понимание того, как производится знание, в том числе знание о производстве знания, и суммирует все достижения современной эпистемологии и истории науки, в первую очередь эпистемологии визуального, или Visual Science and Technology Studies. Исходя из этого, делается вывод, что, помимо изучения объективности, авторы изобретают новый способ говорения о науке. Визуальное в науке, со всеми возможными способами его практиковать, позволяет авторам, так или иначе двигающимся в русле прагматических подходов, избежать экстерналистских вариантов объяснений производства знания. Это достигается благодаря тому, что исследователи рассматривают не какие-то локальные визуализации, но работают с целыми ассамбляжами образов, исходя из предпосылки, что визуальное – неотчуждаемая часть науки. Чтобы разобраться с тем, что из себя представляет «Объективность», невозможно не обратиться к работам, которые также исследуют визуальное. Оказалось важным продемонстрировать, что современные исследования зачастую проводятся на стыке разных дисциплин, причем предполагается, что строгие дисциплинарные различия для данных исследований столь же реальны, как и пасторальные идеалы. Возвращая статус отчужденным научным компонентам, подобные подходы демонстрируют, что наука отнюдь не сводится к каким-то исключительно априорным или трансцендентальным пропозициям. Напротив, подтверждается, что наука делается здесь и сейчас и невероятно близка к нам, а это значит, что нельзя просто так пройти мимо любого из практикуемых ею элементов. Unlike the visual as a component of scientific practices, the study of scientific visualizations is a young field of epistemology that has only recently begun to gain momentum. Despite its “young” age, this field of research has already been enriched by all kinds of approaches, concepts, and independent conclusions. In my opinion, Peter Galison and Lorraine Daston’s book Objectivity can be considered as a work which, besides bringing obvious innovations in understanding how knowledge is produced, including knowledge about knowledge production, summarizes all achievements of modern epistemology and history of science, first of all, epistemology of the visual or VSTS (Visual Science and Technology Studies). From this it can be inferred that, among other things, in addition to the study of objectivity, the authors are inventing a new way of speaking about science. The visual in science, with all the possible ways of practicing it, allows the authors, moving in one way or another in the direction of pragmatic approaches, to avoid externalistic versions of explanations of knowledge production. This is achieved by the fact that the researchers do not look at some local visualizations, but work with whole assemblages of images, based on the premise that the visual is an inalienable part of science. In order to understand what Objectivity is, one must refer to works that also investigate the visual. It turned out to be important to demonstrate that contemporary research often takes place at the junction of different disciplines, with the assumption that strict disciplinary distinctions for this research are as real as pastoral ideals. By reclaiming the status of alienated scientific components, such approaches demonstrate that science is by no means reducible to some exclusively a priori or transcendental propositions. On the contrary, it confirms that science is done here and now, and is incredibly close to us, which means that one cannot simply pass by any of the elements it practices.

Assessing Visual Science Literacy Using Functional Near-Infrared Spectroscopy with an Artificial Neural Network

The primary barrier to understanding visual and abstract information in STEM fields is representational competence the ability to generate, transform, analyze and explain representations. The relationship is known between the foundational visual literacy and the domain specific science literacy, however how science literacy is a function of science learning is still not well understood despite investigation across many fields. To support the improvement of students’ representational competence and promote learning in science, identification of visualization skills is necessary. This project details the development of an artificial neural network (ANN) capable of measuring and modeling visual science literacy (VSL) via neurological measurements using functional near infrared spectrometry (fNIRS). The developed model has the capacity to classify levels of scientific visual literacy allowing educators and curriculum designers the ability to create more targeted and immersive classroom resources such as virtual reality, to enhance the fundamental visual tools in science.

Research progress on meibomian gland dysfunction from 2011 to 2020: a bibliometric and visualized analysis

Background To explore the research areas, hotspots, and progress of meibomian gland dysfunction through bibliometrics. Methods Related publications were retrieved from the Web of Science Core Collection from 2011 to 2020. VOSviewer1.6.16, Citespace.5.7.R2, and GraphPad Prism 8 were used to visualize the distribution of countries, research institutions, journals, authors, keywords, and annual publication numbers in this field. Results A total number of 716 relevant publications were retrieved. The United States and Keio University ranked the first among the countries and organizations with the most publications. Cornea, Investigative Ophthalmology & Visual Science, and Ocular Surface were the top three journals with the highest publication counts and citations. The authors who contributed to this topic mainly formed three clusters which manifested the research areas, and the extracted keywords mainly formed four clusters which manifested the hotspots were explored. Conclusions The research areas and hotspots of meibomian gland dysfunction were as follow: (1) Pathogenesis or potential etiology of meibomian gland dysfunction; (2) Diagnosis of meibomian gland dysfunction; (3) Therapy of meibomian gland dysfunction and the International Workshop`s dedication to it; (4) Epidemiology of meibomian gland dysfunction.

Mapping Research Trends of Uveal Melanoma: A Bibliometric Analysis

Background: To explore the research trends for uveal melanoma (UM) with bibliometric methods using Web of Science Core Collection (WoSCC) and PubMed (PM).Methods: To find UM-related studies, “uveal melanoma” was used as search term in the WoSCC and PM for the period time from 2000 to 2020. Bibliographic coupling analysis was used to investigate the journals with the highest number of UM-related publications. VOSviewer (VV) was used for mapping the knowledge domain and visualizing the co-occurrence of terms, authors, organizations, countries, co-citation literature, and keywords. The knowledge map based on WoSCC and PM were compared.Results: In the WoSCC 3,748 articles were found, while in PM the search resulted in 3,403 articles. The number of original articles has steadily grown in general in the past two decades. The top ten authors were contributing to 23% (n= 856) of all publications, while the top 10 institutions published 41% (n= 1524) of all articles. The top 3 journals with the highest number of publications for UM-related research included Investigative ophthalmology & visual science, Ophthalmology, and British Journal of Ophthalmology. Co-occurrence analysis based on author keywords showed 6 clusters. The most frequent keywords included metastasis, prognosis, and brachytherapy. The latest research hotspots focused on BAP1, immunotherapy and GNAQ.Conclusions: Genetics and immunology are the latest research frontiers in uveal melanoma. There is a clear need for interdisciplinary, molecular and clinical research approaches to improve the fatal prognosis of uveal melanoma patients.

A new innovative method for model efficiency performance

In every aspect of scientific research, model predictions need calibration and validation as their representativity of the record measurement. In the literature, there are a myriad of formulations, empirical expressions, algorithms and software for model efficiency assessment. In general, model predictions are curve fitting procedures with a set of assumptions that are not cared for sensitively in many studies, but only a single value comparison between the measurements and predictions is taken into consideration, and then the researcher makes the decision as for the model efficiency. Among the classical statistical efficiency formulations, the most widely used ones are bias (BI), mean square error (MSE), correlation coefficient (CC) and Nash-Sutcliffe efficiency (NSE) procedures all of which are embedded within the visual inspection and numerical analysis (VINAM) square graph as measurements versus predictions scatter diagram. The VINAM provides a set of verbal interpretations and then numerical improvements embracing all the previous statistical efficiency formulations. The fundamental criterion in the VINAM is 1:1 (45°) main diagonal along which all visual, science philosophical, logical, rational and mathematical procedures boil down for model validation. The application of the VINAM approach is presented for artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS) model predictions.

Pengaruh Kekontrasan Optotype Snellen Terhadap Tajam Penglihatan Pada Pemeriksaan Refraksi Subjektif

The visual acuity examination is affected by the contrast between the background of the optotype used and the letter. Changes in contrast result in unstable visual acuity and affect the examination results subjectively. The writing of this paper uses a descriptive method using a variety of literature data, one of which is by David Cline, John R. Hofstetter and Henry W., Griffin, with the title. Dictionary Of Visual Science, Fourth Edition which explains that contrast in Snellen's optotype affects visual acuity.