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.

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.

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.

Patients Involved in Funding Research.A Look Back at the Unique Experience of the ECLAIR Working Group of Canceropole CLARA

This article aims to share an innovative experience of organizing and funding research involving those most directly affected:patients.The“ECLAIR”working group of the Canceropole Lyon Auvergne-Rhone-Alpes(CLARA)was created at the end of 2020 with the goal of contributing to the development of a call for projects on the patient experience in oncology,which was launched in January 2021.Initially composed of 8 members,including 7 patients,coordinated by a project manager from CLARA,the ECLAIR working group actively participated in drafting the specifications of the call for projects,developing the eligibility criteria for applications,revising the evaluation and selection criteria for projects,and monitoring the selected projects.This experience was repeated twice.With significant freedom of action,the working group made two decisions that strongly demonstrate the commitment to supporting research partnerships and the active involvement of those affected:firstly,by making partnership a mandatory requirement for the eligibility of applications,and secondly,by conducting the selection of projects themselves,after an independent scientific evaluation phase.Seeking to shed light on the“black box”of partnership,the article also presents the concrete modalities of interaction among the working group members,the adjustments made between different editions of the call for projects,and the relationships maintained with CLARA.

The Association between Researchers’Conceptions of Research and Their Strategic Research Agendas

Purpose:In studies of the research process,the association between how researchers conceptualize research and their strategic research agendas has been largely overlooked.This study aims to address this gap.Design/methodology/approach:This study analyzes this relationship using a dataset of more than 8,500 researchers across all scientific fields and the globe.It studies the associations between the dimensions of two inventories:the Conceptions of Research Inventory(CoRI)and the Multi-Dimensional Research Agenda Inventory—Revised(MDRAI-R).Findings:The findings show a relatively strong association between researchers’conceptions of research and their research agendas.While all conceptions of research are positively related to scientific ambition,the findings are mixed regarding how the dimensions of the two inventories relate to one another,which is significant for those seeking to understand the knowledge production process better.Research limitations:The study relies on self-reported data,which always carries a risk of response bias.Practical implications:The findings provide a greater understanding of the inner workings of knowledge processes and indicate that the two inventories,whether used individually or in combination,may provide complementary analytical perspectives to research performance indicators.They may thus offer important insights for managers of research environments regarding how to assess the research culture,beliefs,and conceptualizations of individual researchers and research teams when designing strategies to promote specific institutional research focuses and strategies.Originality/value:To the best of the authors’knowledge,this is the first study to associate research agendas and conceptions of research.It is based on a large sample of researchers working worldwide and in all fields of knowledge,which ensures that the findings have a reasonable degree of generalizability to the global population of researchers.

Biobanks and biomarkers:Their current and future role in biomedical research

The importance and utility of biobanks has increased exponentially since their inception and creation.Initially used as part of translational research,they now contribute over 40%of data for all cancer research papers in the United States of America and play a crucial role in all aspects of healthcare.Multiple classification systems exist but a simplified approach is to either classify as population-based or disease-oriented entities.Whilst historically publicly funded institutions,there has been a significant increase in industry funded entities across the world which has changed the dynamic of biobanks offering new possibilities but also new challenges.Biobanks face legal questions over data sharing and intellectual property as well as ethical and sustainability questions particularly as the world attempts to move to a low-carbon economy.International collaboration is required to address some of these challenges but this in itself is fraught with complexity and difficulty.This review will examine the current utility of biobanks in the modern healthcare setting as well as the current and future challenges these vital institutions face.

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.

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.

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.

Brain Research on Mental Disorders: A Criticism

Objective: To expose the problems and inherent limitations of neuroscience-based brain research on mental disorders. Method: Discussion of the theory underlying brain research on mental disorders, followed by a systematic evaluation of typical studies. Results: The fundamental problem is that brain researchers fail to differentiate between biological mental disorders in which brain processes cause the disorder (notably schizophrenia, bipolar disorder, and melancholic depression) and learned mental disorders in which brain processes mediate but do not cause the disorder (which is the case with reactive depression, reactive anxiety, OCD, and PTSD). Researchers have been unsuccessful in identifying mechanisms in the brain that cause biological mental disorders, and will never be able to locate the innumerable specific neural connections that mediate learned mental disorders. Moreover, the author’s review of typical studies in this field shows that they have serious problems with theory, measurement, and data analysis, and that their findings cannot be trusted. Conclusions: Neuroscience-based brain research on mental disorders, unlike other neurological research, has been an expensive failure and it is not worth continuing.

Visual Analysis of Domestic and Foreign Building Brick Skin Research Based on Citespace

With the progress of the times and the leap of science and technology,the application of brick materials and the research on the brick skin in modern architectural design have shown a dual-track development trend of returning to tradition and innovation.Based on the core collection database resources of Web of Science and the CiteSpace visual analysis tool,this paper constructed and analyzed the spatio-temporal map of keyword co-occurrence network,cluster structure,mutation phenomenon,time course and regional distribution map of building brick skin research.The study revealed that in recent years,the research on brick materials has spanned the study of single material properties and extensively involved in the broad world of construction,especially in the integration of green energy-saving technology,the innovation of fine construction technology of brick skin,and the frontier exploration of digital technology in brick masonry,which has shown particularly significant research vitality and development potential.

Research Characteristics of Thermal Comfort of Urban Block Landscape Based on Knowledge Graph Analysis

The landscape environment of urban blocks plays a significant role in improving the comfort of urban thermal environment and promoting green and high-quality development.The 342 papers related to the research on the impact of urban block landscape environment on thermal comfort in China,collected by CNKI(China National Knowledge Infrastructure)from 2002 to 2022,are used as the research object.Through bibliometric statistical analysis,LLR algorithm,and cluster analysis,the current research status of the impact of urban block landscape environment on thermal comfort in China is analyzed and processed,and its external characteristics are identified.Using the information visualization software CiteSpace,the research topics in the field of the impact of urban block landscape environment on thermal comfort are presented in the form of knowledge graphs.Through co-occurrence analysis of keywords and trend of word frequency changes,the development trends of research hotspots and cutting-edge fields of the impact of urban block landscape environment on thermal comfort are determined,hoping to provide reference for future research in this field.

What are Different Research Approaches?Comprehensive Review of Qualitative,Quantitative,and Mixed Method Research,Their Applications,Types,and Limitations

There are different ways to examine and explain a study and its findings based on using numbers as a measure,a descriptive style,or a mixture of both.These three research approaches are quantitative,qualitative,and mixed methods that are commonly used by researchers in various research studies.However,with many options regarding the research design,it seems challenging for researchers to select the most appropriate approach based on the study and realize differences.This study provides a comprehensive review of qualitative,quantitative,and mixed-method research methods.Each method is clearly defined and specifically discussed based on applications,types,advantages,and limitations to help researchers identify select the most relevant type based on each study and navigate accordingly.

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.

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.

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。

New roles of research data infrastructure in research paradigm evolution

Research data infrastructures form the cornerstone in both cyber and physical spaces,driving the progression of the data-intensive scientific research paradigm.This opinion paper presents an overview of global research data infrastructure,drawing insights from national roadmaps and strategic documents related to research data infrastructure.It emphasizes the pivotal role of research data infrastructures by delineating four new missions aimed at positioning them at the core of the current scientific research and communication ecosystem.The four new missions of research data infrastructures are:(1)as a pioneer,to transcend the disciplinary border and address complex,cutting-edge scientific and social challenges with problem-and data-oriented insights;(2)as an architect,to establish a digital,intelligent,flexible research and knowledge services environment;(3)as a platform,to foster the high-end academic communication;(4)as a coordinator,to balance scientific openness with ethics needs.

Global Scientific Trends in Research Related to Diabetic Sarcopenia from 1993 to 2023: A Bibliometric Analysis

Objectives: In this study, bibliometric approach was used to explore the literature in the field of research related to Diabetic Myasthenia Gravis in order to identify the current research progress in Diabetic Myasthenia Gravis related research and to help the researchers to predict the future hotspots in the field of research and to provide reference for the research. Methods: Literature related to diabetic sarcopenia published from 1993 to 2023 since the inception of the repository was extracted from the Web of Science Core Collection (WoSCC) and bibliometric analyses were performed. We have analysed the published literature of the last approximately almost 30 years, as well as publication and citation analyses from different countries, institutions, journals and authors. For keywords, we performed co-occurrence, clustering, timeline view and citation burst analysis. Results: On the basis of 1564 publications, we found a continuous increase in the number of publications and citations, especially in the last six years. The United States is the most representative country, and Seoul National University (SNU) is the most representative institution. The most popular journal in the field is Diabetes Care;Fukui, Michiaki is the most prolific author, leading many studies related to diabetic sarcopenia. The most frequently cited reference was a revised European consensus on the definition and diagnosis of sarcopenia;the most cited keywords were related to physiological factors of diabetes, sarcopenia and related conditions, such as “insulin resistance”, “skeletal muscle”, “body composition”, “risk” and “prevalence”. Conclusion: With more and more studies on the relationship between diabetic sarcopenia, this study presents the current status and trend of research related to diabetic sarcopenia over the past nearly 30 years through the visualization software CiteSpace. It can help researchers identify potential collaborators and partner institutions, hotspots and research frontiers in the field of diabetic sarcopenia. However, our work is only based on the English language literature in the WoSCC database, and for future studies, we recommend that researchers explore the literature from multiple databases to enhance the scope of their research.