Machine learning applications in healthcare clinical practice and research

Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.

Synthetic data as an investigative tool in hypertension and renal diseases research

There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient privacy.This is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension worldwide.However,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.

Harnessing artificial intelligence for identifying conflicts of interest in research

This editorial explores the transformative potential of artificial intelligence(AI)in identifying conflicts of interest(COIs)within academic and scientific research.By harnessing advanced data analysis,pattern recognition,and natural language processing techniques,AI offers innovative solutions for enhancing transparency and integrity in research.This editorial discusses how AI can automatically detect COIs,integrate data from various sources,and streamline reporting processes,thereby maintaining the credibility of scientific findings.

A Reviewing on English Writing Researching in China

English writing is also a crucial means of evaluating the language proficiency of a learner of English as second language.As a result, it is essential to review English writing researching in terms of contents, number, methods, process, feedback and assessment which can guide our English writing teaching effectively.

Researching Classroom-Based Assessment for Formative Purposes

This article aims to help teacher-researchers engage in empirical research on classroom-based assessment for formative purposes. We will first introduce the key features of classroom-based formative assessment(CBFA), and analyze the research questions asked in round-one projects funded by the Fund for Assessment Research(FAR) in Foreign Language Education in China. Next, we will illustrate how some research questions can be answered by analyzing a video-taped lesson from a round-one FAR project. We conclude by calling for more teacher-led research and argue that research on CBFA by teachers will not only produce valid interpretations and applicable findings, but also constitute a viable model for teacher professional development.

跨学科口笔译研究的百科全书——Researching Translation and Interpreting介评

劳特里奇出版社2016年推出的Researching Translation and Interpreting一书以综合开阔的研究视野和跨学科融合的研究范式,广泛吸收与借鉴了社会学、文化学、人类学、语言学、认知科学、心理学、历史学、教育学等多个相关学科的研究成果,全面建构起口笔译研究的路线图和方法论,为读者提供了比以往论著更全更新的研究视角和方法指南,堪称跨学科口笔译研究的百科全书。该书对丰富和完善口笔译研究的理论与方法,促进和推动翻译学的学科发展具有重要的参考价值和指导意义。本文拟对这一著作进行介绍,并在此基础上分析其学术特色及贡献,指出存在的局限和不足,旨在为国内口笔译研究提供借鉴和启示。

Research funding and citations in papers of Nobel Laureates in Physics, Chemistry and Medicine, 2019-2020

Purpose:The goal of this study is a comparative analysis of the relation between funding(a main driver for scientific research)and citations in papers of Nobel Laureates in physics,chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole.Design/methodology/approach:This study utilizes a power law model to explore the relationship between research funding and citations of related papers.The study here analyzes 3,539 recorded documents by Nobel Laureates in physics,chemistry and medicine and a broader dataset of 183,016 documents related to the fields of physics,medicine,and chemistry recorded in the Web of Science database.Findings:Results reveal that in chemistry and medicine,funded researches published in papers of Nobel Laureates have higher citations than unfunded studies published in articles;vice versa high citations of Nobel Laureates in physics are for unfunded studies published in papers.Instead,when overall data of publications and citations in physics,chemistry and medicine are analyzed,all papers based on funded researches show higher citations than unfunded ones.Originality/value:Results clarify the driving role of research funding for science diffusion that are systematized in general properties:a)articles concerning funded researches receive more citations than(un)funded studies published in papers of physics,chemistry and medicine sciences,generating a high Matthew effect(a higher growth of citations with the increase in the number of papers);b)research funding increases the citations of articles in fields oriented to applied research(e.g.,chemistry and medicine)more than fields oriented towards basic research(e.g.,physics).Practical implications:The results here explain some characteristics of scientific development and diffusion,highlighting the critical role of research funding in fostering citations and the expansion of scientific knowledge.This finding can support decision-making of policymakers and R&D managers to improve the effectiveness in allocating financial resources in science policies to generate a higher positive scientific and societal impact.

General laws of funding for scientific citations:how citations change in funded and unfunded research between basic and applied sciences

Purpose:The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences.Design/methodology/approach:A power law model analyzes the relationship between research funding and citations of papers using 831,337 documents recorded in the Web of Science database.Findings:The original results reveal general characteristics of the diffusion of science in research fields:a)Funded articles receive higher citations compared to unfunded papers in journals;b)Funded articles exhibit a super-linear growth in citations,surpassing the increase seen in unfunded articles.This finding reveals a higher diffusion of scientific knowledge in funded articles.Moreover,c)funded articles in both basic and applied sciences demonstrate a similar expected change in citations,equivalent to about 1.23%,when the number of funded papers increases by 1%in journals.This result suggests,for the first time,that funding effect of scientific research is an invariant driver,irrespective of the nature of the basic or applied sciences.Originality/value:This evidence suggests empirical laws of funding for scientific citations that explain the importance of robust funding mechanisms for achieving impactful research outcomes in science and society.These findings here also highlight that funding for scientific research is a critical driving force in supporting citations and the dissemination of scientific knowledge in recorded documents in both basic and applied sciences.Practical implications:This comprehensive result provides a holistic view of the relationship between funding and citation performance in science to guide policymakers and R&D managers with science policies by directing funding to research in promoting the scientific development and higher diffusion of results for the progress of human society.

Research Progress and Prospects of Total Factor Productivity in the Construction Industry

The high-quality development of the construction industry fundamentally stems from the significant improvement of total factor productivity.Therefore,it is of crucial significance for promoting the development of the construction industry to a higher level by scientifically and accurately measuring the total factor productivity of the construction industry and deeply analyzing the influencing factors behind it.Based on a comprehensive consideration of research methods and influencing factors,this paper systematically reviews the existing relevant literature on total factor productivity in the construction industry,aiming to reveal the current research development trend in this field and point out potential problems.This effort aims to provide a solid theoretical foundation and valuable reference for further in-depth research,and jointly promote the continuous progress and development of total factor productivity research in the construction industry.

The Industrial Heritage and the New Architecture： Teaching, Researching, Designing the Place Identity

The new architecture may provide unusual opportunities for the abandoned areas involved by former industrial processes, both in the city centers and in the landscape. In fact, it may create new centralities and give new collective function for deprived areas. The case study of the architectural and educational project for a new museum park devoted to the technique and the science in the Apennine＇ s landscape near Parma （Italy） may give an interesting point of view about the role of the teaching and the research of the architecture in the former industrial heritage, and to avoid the abandonment and the pauperization of the territory around.

Recent Ventures in Interdisciplinary Arctic Research:The ARCPATH Project

This paper celebrates Professor Yongqi GAO's significant achievement in the field of interdisciplinary studies within the context of his final research project Arctic Climate Predictions: Pathways to Resilient Sustainable Societies-ARCPATH(https://www.svs.is/en/projects/finished-projects/arcpath). The disciplines represented in the project are related to climatology, anthropology, marine biology, economics, and the broad spectrum of social-ecological studies. Team members were drawn from the Nordic countries, Russia, China, the United States, and Canada. The project was transdisciplinary as well as interdisciplinary as it included collaboration with local knowledge holders. ARCPATH made significant contributions to Arctic research through an improved understanding of the mechanisms that drive climate variability in the Arctic. In tandem with this research, a combination of historical investigations and social, economic, and marine biological fieldwork was carried out for the project study areas of Iceland, Greenland, Norway, and the surrounding seas, with a focus on the joint use of ocean and sea-ice data as well as social-ecological drivers. ARCPATH was able to provide an improved framework for predicting the near-term variation of Arctic climate on spatial scales relevant to society, as well as evaluating possible related changes in socioeconomic realms. In summary, through the integration of information from several different disciplines and research approaches, ARCPATH served to create new and valuable knowledge on crucial issues, thus providing new pathways to action for Arctic communities.

Optimization process of compiling and researching archivesin universities under the background of information sharing

Intemet era, mutual sharing, low cost, unlimited time and geographical restrictions on network dissemination, to the public toprovide a new way of entertainment experience and sharing in the network information resources at the same time, also highlights importantdrawbacks, mainly reflected the contradiction between resource sharing and copyright protection, sharing is often cyber source violated theright to network dissemination of information to the original author. With the rapid development of the Internet, the seriousness of this problemis becoming increasingly prominent. Based on the information construction of university archives management as the center to carry outresearch, improve the service level of university archives from the first two aspects discusses the necessity of the information constructionof the archives management, promoting the development of colleges and universities. Secondly introduces specific measures of realizing theinformatization construction of university archives management and archives management standardization, digitization, archives informationnetwork construction, the archives management personnel to conduct a comprehensive training. The fixed assets of university is an important partof the state-owned assets, and its asset management level is directly related to the safety of state-owned assets, the use efficiency of assets and thepromotion of the teaching and research level in universities. The university fixed assets data information management is an important aspect ofasset management, it provides decision-making basis for the management of fixed assets in colleges and universities, affecting the efficiency ofthe entire asset management.

Behind the Scenes with a Video Training Platform: The Challenges of Researching the Provision of Open Educational Resources

Video training platforms are now being implemented on a large scale in organizations. In this paper, I look at a video training platform including open educational resources available for many employees with varying patterns and motivations for use. This has provided me with a research challenge to find methods that help other practitioners in the field understand and explain such initiatives. I describe ways to model the research and identify where pressures and contradictions can be found, drawing on a reflective view of my own practice in performing the research. Open educational resources are defined as technology-enabled educational resources that are openly available for consultation, use and adaptation by users for non-commercial purposes [1]. The bank subject to this case study has been the first organisation in Turkey that provided open educational resources for all its employees. The video platform (called “For @ Tube”) provides users with over 100 video lectures drawn from reputable universities around the world including Yale and Harvard. Other learning tools such as discussion forums, blogs and traditional e-learning courses have been made available to the users on the e-learning platform called “For @” since 2006. In this paper, I aim to introduce the new video training platform (“For @ Tube”) and outline some of the main research issues surrounding such an initiative. I seek to explore theoretical and practical approaches that can provide suitable tools for analysis. Activity theory is seen as a suitable approach for macroanalysis and its use is illustrated in terms of the complexity of large scale research. Activity theory, besides informing research perspectives, can be turned in upon the research process itself, allowing us to consider the challenges and context of the research. By using activity theory in this way and illustrating from a range of practical approaches, I demonstrate and illustrate a useful research approach.

Preschool Child＇s Researching Interests and Role of Visual Art＇s Expressing Media

Genuine interest, research zeal, and visual art expressiveness which are typical of the pre-school period can pose a challenge to every teacher, at the same time, guide them when planning different contents for children to explore and discover. As one of the primary expressing media and an important support when forming concepts, visual art plays an indispensable role in the pre-school period. The following thesis is based on an action research whose key tendencies were focused on establishing children＇s interests in different useful materials and tools while enabling them an autonomous visual art use of these tools and didactical possibilities of the teacher involved. The activities included in the research were fully in line with the Slovenian National Kindergarten Curriculum and the project was carried out in the form of several successive meetings intended for visual art creative activities. All activities in the research were photo-documented while the analysis of the research＇s data was performed based on observation and written notes referring to individual child＇s responses, his or her questions, ideas, and incentives, the course of cognitive and creative process, communication with the peers and teachers and other potential particularities.

Researching the Research: Applying Machine Learning Techniques to Dissertation Classification

This research examines industry-based dissertation research in a doctoralcomputing program through the lens of machine learning algorithms todetermine if natural language processing-based categorization on abstractsalone is adequate for classification. This research categorizes dissertationby both their abstracts and by their full-text using the GraphLabCreate library from Apple’s Turi to identify if abstract analysis is anadequate measure of content categorization, which we found was not. Wealso compare the dissertation categorizations using IBM’s Watson Discoverydeep machine learning tool. Our research provides perspectiveson the practicality of the manual classification of technical documents;and, it provides insights into the: (1) categories of academic work createdby experienced fulltime working professionals in a Computing doctoralprogram, (2) viability and performance of automated categorization of theabstract analysis against the fulltext dissertation analysis, and (3) natuallanguage processing versus human manual text classification abstraction.

Can ChatGPT evaluate research quality?

Purpose:Assess whether ChatGPT 4.0 is accurate enough to perform research evaluations on journal articles to automate this time-consuming task.Design/methodology/approach:Test the extent to which ChatGPT-4 can assess the quality of journal articles using a case study of the published scoring guidelines of the UK Research Excellence Framework(REF)2021 to create a research evaluation ChatGPT.This was applied to 51 of my own articles and compared against my own quality judgements.Findings:ChatGPT-4 can produce plausible document summaries and quality evaluation rationales that match the REF criteria.Its overall scores have weak correlations with my self-evaluation scores of the same documents(averaging r=0.281 over 15 iterations,with 8 being statistically significantly different from 0).In contrast,the average scores from the 15 iterations produced a statistically significant positive correlation of 0.509.Thus,averaging scores from multiple ChatGPT-4 rounds seems more effective than individual scores.The positive correlation may be due to ChatGPT being able to extract the author’s significance,rigour,and originality claims from inside each paper.If my weakest articles are removed,then the correlation with average scores(r=0.200)falls below statistical significance,suggesting that ChatGPT struggles to make fine-grained evaluations.Research limitations:The data is self-evaluations of a convenience sample of articles from one academic in one field.Practical implications:Overall,ChatGPT does not yet seem to be accurate enough to be trusted for any formal or informal research quality evaluation tasks.Research evaluators,including journal editors,should therefore take steps to control its use.Originality/value:This is the first published attempt at post-publication expert review accuracy testing for ChatGPT.

Global trends in diabetic eye disease research from 2012 to 2021

Diabetic eye disease refers to a group of eye complications that occur in diabetic patients and include diabetic retinopathy, diabetic macular edema, diabetic cataracts, and diabetic glaucoma. However, the global epidemiology of these conditions has not been well characterized. In this study, we collected information on diabetic eye disease-related research grants from seven representative countries––the United States, China, Japan, the United Kingdom, Spain, Germany, and France––by searching for all global diabetic eye disease journal articles in the Web of Science and Pub Med databases, all global registered clinical trials in the Clinical Trials database, and new drugs approved by the United States, China, Japan, and EU agencies from 2012 to 2021. During this time period, diabetic retinopathy accounted for the vast majority(89.53%) of the 2288 government research grants that were funded to investigate diabetic eye disease, followed by diabetic macular edema(9.27%). The United States granted the most research funding for diabetic eye disease out of the seven countries assessed. The research objectives of grants focusing on diabetic retinopathy and diabetic macular edema differed by country. Additionally, the United States was dominant in terms of research output, publishing 17.53% of global papers about diabetic eye disease and receiving 22.58% of total citations. The United States and the United Kingdom led international collaborations in research into diabetic eye disease. Of the 415 clinical trials that we identified, diabetic macular edema was the major disease that was targeted for drug development(58.19%). Approximately half of the trials(49.13%) pertained to angiogenesis. However, few drugs were approved for ophthalmic(40 out of 1830;2.19%) and diabetic eye disease(3 out of 1830;0.02%) applications. Our findings show that basic and translational research related to diabetic eye disease in the past decade has not been highly active, and has yielded few new treatment methods and newly approved drugs.

关于现阶段我国英文期刊办刊模式的思考——以Research等期刊为例

近年来,国内兴起了创办英文科技期刊热潮。本文以此为视角,分析了我国创办英文期刊现状及问题。通过查阅文献和新闻报道,以中国科协和美国科学促进会合作共同创办的英文期刊Research等近年来国内创办的高水平英文新刊为例,详细分析了案例从创刊到快速发展成为高影响力科技期刊的路径,主要包括选择办刊人才、明确办刊定位、组建编委会、邀约优质稿源、加大媒体宣传等,以期为正在筹备创办新刊的同行提供借鉴,也为相关部门决策提供建议参考。

Researching the Classroom

This paper explains how any teacher can do their own classroom research as a part of their normal teaching.In order to research the classroom,it reviews some teacher’s questions in the classroom.After introducing two ways of researching:research by thinking and research by experimenting,the paper analyses the reasons and shows some methods to solve the problems.This will determine the shape of what is done in the classroom exactly.It’s helpful for the teachers to have lessons every day.

Citation distributions and research evaluations:The impossibility of formulating a universal indicator

Purpose:To analyze the diversity of citation distributions to publications in different research topics to investigate the accuracy of size-independent,rank-based indicators.The top percentile-based indicators are the most common indicators of this type,and the evaluations of Japan are the most evident misjudgments.Design/methodology/approach:The distributions of citations to publications from countries and journals in several research topics were analyzed along with the corresponding global publications using histograms with logarithmic binning,double rank plots,and normal probability plots of log-transformed numbers of citations.Findings:Size-independent,top percentile-based indicators are accurate when the global ranks of local publications fit a power law,but deviations in the least cited papers are frequent in countries and occur in all journals with high impact factors.In these cases,a single indicator is misleading.Comparisons of the proportions of uncited papers are the best way to predict these deviations.Research limitations:This study is fundamentally analytical,and its results describe mathematical facts that are self-evident.Practical implications:Respectable institutions,such as the OECD,the European Commission,and the U.S.National Science Board,produce research country rankings and individual evaluations using size-independent percentile indicators that are misleading in many countries.These misleading evaluations should be discontinued because they can cause confusion among research policymakers and lead to incorrect research policies.Originality/value:Studies linking the lower tail of citation distribution,including uncited papers,to percentile research indicators have not been performed previously.The present results demonstrate that studies of this type are necessary to find reliable procedures for research assessments.