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.

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.

Glucocorticoids-based prodrug design:Current strategies and research progress

Attributing to their broad pharmacological effects encompassing anti-inflammation,antitoxin,and immunosuppression,glucocorticoids(GCs)are extensively utilized in the clinic for the treatment of diverse diseases such as lupus erythematosus,nephritis,arthritis,ulcerative colitis,asthma,keratitis,macular edema,and leukemia.However,longterm use often causes undesirable side effects,including metabolic disorders-induced Cushing's syndrome(buffalo back,full moon face,hyperglycemia,etc.),osteoporosis,aggravated infection,psychosis,glaucoma,and cataract.These notorious side effects seriously compromise patients'quality of life,especially in patients with chronic diseases.Therefore,glucocorticoid-based advanced drug delivery systems for reducing adverse effects have received extensive attention.Among them,prodrugs have the advantages of low investment,low risk,and high success rate,making them a promising strategy.In this review,we propose the strategies for the design and summarize current research progress of glucocorticoid-based prodrugs in recent decades,including polymer-based prodrugs,dendrimer-based prodrugs,antibody-drug conjugates,peptide-drug conjugates,carbohydrate-based prodrugs,aliphatic acid-based prodrugs and so on.Besides,we also raise issues that need to be focused on during the development of glucocorticoid-based prodrugs.This review is expected to be helpful for the research and development of novel GCs and prodrugs.

Global research trends and hotspots in overweight/obese comorbid with depression among children and adolescents: A bibliometric analysis

BACKGROUND Overweight/obesity combined with depression among children and adolescents(ODCA)is a global concern.The bidirectional relationship between depression and overweight/obesity often leads to their comorbidity.Childhood and adolescence represent critical periods for physical and psychological development,during which the comorbidity of overweight/obesity and depression may increase the risk of adverse health outcomes.AIM To evaluate the relationship between ODCA,we conduct a bibliometric analysis to aid in formulating prevention and treatment strategies.METHODS From 2004 to 2023,articles related to ODCA were selected using the Science Citation Index Expanded from the Web of Science Core Collection.Bibliometric analysis of relevant publications,including countries/regions,institutions,authors,journals,references,and keywords,was conducted using the online bibliometric analysis platforms,CiteSpace,VOSviewer,and bibliometrix.RESULTS Between 2004 and 2023,a total of 1573 articles were published on ODCA.The United States has made leading contributions in this field,with Harvard University emerging as the leading contributor in terms of research output,and Tanofsky being the most prolific author.The J Adolescent Health has shown significant activity in this domain.Based on the results of the keyword and reference analyses,inequality,adverse childhood experiences,and comorbidities have become hot topics in ODCA.Moreover,the impact of balancedrelated behavior and exploration of the biological mechanisms,including the potential role of key adipocytokines and lipokines,as well as inflammation in ODCA,have emerged as frontier topics.CONCLUSION The trend of a significant increase in ODCA publications is expected to continue.The research findings will contribute to elucidating the pathogenic mechanisms of ODCA and its prevention and treatment.

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.

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。

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.

Most bird species remain poorly studied but threated status promotes research effort

To halt biodiversity loss,threatened species are often selected as targets for conservation actions.However,whether most threatened species receive sufficient research effort remains unknown.Low research and public attention of threatened species would hinder the implementation of effective conservation actions.Therefore,it is urgent to assess both research effort and species extinction risk simultaneously to provide critical information for targeted conservation practices.Here,we evaluated research effort of extant bird species worldwide(n 10,904)by searching the number of all publications and those focused on conservation in Scopus database fo=r each species,and investigated key determinants of research effort.We found that although the median value of publications of threatened species was significantly higher than that of non-threatened species,47.4%of threatened species had less than 3 publications,and 73.8%had less than 10 publications,indicating low research effort of most threatened species.Although research effort was positively related to extinction risk,research effort was mainly associated with human-related variables,with birds described earlier and occurred in developed regions receiving higher research effort.In comparison,extinction risk was mainly associated with biological attributes,with large-sized and narrow-distributed species being more likely to be threatened.Our finding suggests that research effort of species can provide complementary information for current conservation strategies designed for threatened species,and we urge that many recently discovered and narrowly distributed species in less developed regions require more research and conservation attention.

Applications and advancements in animal models for antiviral research on mosquito-borne arboviruses

Vector-borne diseases caused by arthropod-borne viruses(arboviruses) are a considerable challenge to public health globally. Mosquito-borne arboviruses, such as Chikungunya, Dengue, and Zika viruses, cause a range of human illnesses and may be fatal. Currently, efforts to control these diseases still face challenges due to growing vector resistance towards insecticides, urbanization, and limited effective antiviral treatments and vaccines. Animal models are crucial in antiviral research on mosquito-borne arboviruses, playing a role in understanding disease mechanisms,vaccine development, and toxicity testing, but the application of animal models still faces the challenges of ethical considerations and animal-to-human translational success. Genetically engineered mouse models, hamster models and non-human primate(NHP) are currently used in arbovirus research, but new models such as tree shrews and novel humanized mice are emerging. In the context of Malaysian research, the use of long-tailed macaques as potential NHP models for arbovirus research is possible;however, it faces the ethical dilemma of using an endangered species for scientific purposes. Overall, animal models play a crucial role in advancing infectious disease research, but a balance between medical research and species conservation must be upheld.

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.

Navigating interdisciplinary research:Historical progression and contemporary challenges

Interdisciplinary research plays a crucial role in addressing complex problems by integrating knowledge from multiple disciplines.This integration fosters innovative solutions and enhances understanding across various fields.This study explores the historical and sociological development of interdisciplinary research and maps its evolution through three distinct phases:pre-disciplinary,disciplinary,and post-disciplinary.It identifies key internal dynamics,such as disciplinary diversification,reorganization,and innovation,as primary drivers of this evolution.Additionally,this study highlights how external factors,particularly the urgency of World War II and the subsequent political and economic changes,have accelerated its advancement.The rise of interdisciplinary research has significantly reshaped traditional educational paradigms,promoting its integration across different educational levels.However,the inherent contradictions within interdisciplinary research present cognitive,emotional,and institutional challenges for researchers.Meanwhile,finding a balance between the breadth and depth of knowledge remains a critical challenge in interdisciplinary education.

Challenges and Suggestions of Ethical Review on Clinical Research Involving Brain-Computer Interfaces

Brain-computer interface(BCI)technology is rapidly advancing in medical research and application.As an emerging biomedical engineering technology,it has garnered significant attention in the clinical research of brain disease diagnosis and treatment,neurological rehabilitation,and mental health.However,BCI also raises several challenges and ethical concerns in clinical research.In this article,the authors investigate and discuss three aspects of BCI in medicine and healthcare:the state of international ethical governance,multidimensional ethical challenges pertaining to BCI in clinical research,and suggestive concerns for ethical review.Despite the great potential of frontier BCI research and development in the field of medical care,the ethical challenges induced by itself and the complexities of clinical research and brain function have put forward new special fields for ethics in BCI.To ensure"responsible innovation"in BCI research in healthcare and medicine,the creation of an ethical global governance framework and system,along with special guidelines for cutting-edge BCI research in medicine,is suggested.

Tracking direct and indirect impact on technology and policy of transformative research via ego citation network

Purpose:The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers.This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network.Design/methodology/approach:Key Nobel Prize-winning publications(NPs)in fields of gene engineering and astrophysics are regarded as a proxy for transformative research.In this contribution,we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact.Findings:The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics.Research limitations:The selection of Nobel Prizes is not balanced and the database used in this study,Dimensions,suffers from incompleteness and inaccuracy of citation links.Practical implications:Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact.Originality/value:This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.

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.