Visualizing the structure and the evolving of digital medicine: a scientometrics review

Global trends and hotspots in the digital therapeutics of autism spectrum disorders: a bibliometric analysis from 2002 to 2022

Introduction

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that has become a major cause of disability in children. Digital therapeutics (DTx) delivers evidence-based therapeutic interventions to patients that are driven by software to prevent, manage, or treat a medical disorder or disease. This study objectively analyzed the current research status of global DTx in ASD from 2002 to 2022, aiming to explore the current global research status and trends in the field.

Methods

The Web of Science database was searched for articles about DTx in ASD from January 2002 to October 2022. CiteSpace was used to analyze the co-occurrence of keywords in literature, partnerships between authors, institutions, and countries, the sudden occurrence of keywords, clustering of keywords over time, and analysis of references, cited authors, and cited journals.

Results

A total of 509 articles were included. The most productive country and institution were the United States and Vanderbilt University. The largest contributing authors were Warren, Zachary, and Sarkar, Nilanjan. The most-cited journal was the Journal of Autism and Developmental Disorders. The most-cited and co-cited articles were Brian Scarselati (Robots for Use in Autism Research, 2012) and Ralph Adolphs (Abnormal processing of social information from faces in autism, 2001). "Artificial Intelligence," "machine learning," "Virtual Reality," and "eye tracking" were common new and cutting-edge trends in research on DTx in ASD.

Discussion

The use of DTx in ASD is developing rapidly and gaining the attention of researchers worldwide. The publications in this field have increased year by year, mainly concentrated in the developed countries, especially in the United States. Both Vanderbilt University and Yale University are very important institutions in the field. The researcher from Vanderbilt University, Warren and Zachary, his dynamics or achievements in the field is also more worth our attention. The application of new technologies such as virtual reality, machine learning, and eye-tracking in this field has driven the development of DTx on ASD and is currently a popular research topic. More cross-regional and cross-disciplinary collaborations are recommended to advance the development and availability of DTx.

Digital Transformation in Healthcare: Technology Acceptance and Its Applications

Technological innovation has become an integral aspect of our daily life, such as wearable and information technology, virtual reality and the Internet of Things which have contributed to transforming healthcare business and operations. Patients will now have a broader range and more mindful healthcare choices and experience a new era of healthcare with a patient-centric culture. Digital transformation determines personal and institutional health care. This paper aims to analyse the changes taking place in the field of healthcare due to digital transformation. For this purpose, a systematic bibliographic review is performed, utilising Scopus, Science Direct and PubMed databases from 2008 to 2021. Our methodology is based on the approach by Wester and Watson, which classify the related articles based on a concept-centric method and an ad hoc classification system which identify the categories used to describe areas of literature. The search was made during August 2022 and identified 5847 papers, of which 321 fulfilled the inclusion criteria for further process. Finally, by removing and adding additional studies, we ended with 287 articles grouped into five themes: information technology in health, the educational impact of e-health, the acceptance of e-health, telemedicine and security issues.

A Novel Scientometrics Research on the Interaction between Oxidative Stress and Hematopoietic Stem Cell Transplantation Complications: From Graft-versus-Host Disease to Sepsis

As major and serious complications after hematopoietic stem cell transplantation (HSCT), graft-versus-host disease (GVHD) and sepsis are the chief causes of low survival rates as well as mortality and for HSCT recipients. Although the overall treatment outcomes of HSCT have improved significantly in recent years, there is still an increased incidence rate of complications and mortality after transplantation. In the immediate past, with a deeper understanding of oxidative stress, more and more shreds of evidence have shown that it is closely related to transplantation-related sepsis. However, there is currently a precious little research on the interaction between oxidative stress and complications after HSCT, and the major mechanism has not yet been clarified. The objective of this study was to assess the internal connection between and potential mechanisms as well as visualized the scientometrics results of all important literature related to the topic. Through exhaustive scientometrics analysis, we searched and carefully screened 286 related publications from the Web of Science Core Collection (WoSCC) with "((HSCT) OR (hematopoietic stem cell transplantation)) AND (oxidative stress)" as the search strategy. Then, detailed visualization of the overall information analysis was made by scientific and rigorous bibliometrics software or website. Next, we analyzed retrieved articles extensively and then 59 publications that are relevant to this topic were selected for nuanced analysis and summary. The assessment of these studies proved the validity of the interaction between oxidative stress and complications after HSCT objectively and directly.

The evolution of digital health technologies in cardiovascular disease research

When implemented in practice, digital technologies have shown improvements in morbidity and mortality outcomes in patients with cardiovascular disease (CVD). For scholars, research into digital technologies in cardiovascular care has been relatively recent, thus it is important to understand the history of digital health technology in cardiovascular research-its emergence, rate of growth, hot topics, and its temporal evolution. The aim of this study was to analyse more than 16,000 articles in this domain based on their scientometric indicators. Web of Science (WoS) Core Collection was accessed and searched at several levels, including titles, abstracts, keywords, authors, sources and individual articles. Analysis examined the temporal shifts in research and scholarly focus based on keywords, networks of collaboration, topical divisions in relation to digital technologies, and influential publications. Findings showed this research area is growing exponentially. Co-citation analysis revealed twenty prominent research streams and identified variation in the magnitude of activities in each stream. A recent emergence of research activities in digital technology in cardiovascular rehabilitation (CR), out-of-hospital cardiac arrest (OHCA), and arrythmia research was also demonstrated. Conversely, wearable technologies, activity tracking and electronic medical records research are now past their peak of reported research activity. With increasing amounts of novel technologies becoming available and more patients taking part in remote health care monitoring, further evaluation and research into digital technologies, including their long-term effectiveness, is needed. Furthermore, emerging technologies, which are evaluated and/or validated should be considered for implementation into clinical practice as treatment and prevention modalities for CVD.

Evolution of customer relationship management to data mining-based customer relationship management: a scientometric analysis

Scores of researchers have paid attention to empirical and conceptual dimensions of Customer relationship management (CRM). A few studies summarise the research output of CRM focusing on a specific industry. Nevertheless, there is scant literature summarising the research output of CRM in contrast to the data mining-based CRM. This study presents a scientometric analysis that evaluates CRM research output with a special focus on data mining-based CRM. Bibliometric data were extracted for the period 2000-2020 from the Web of Science database to apply descriptive analysis and scientometric analysis to obtain the bibliometric profile of CRM research. Further, we generated the conceptual structure map using multiple correspondence analysis and clustering for CRM and data mining-based CRM research fields. Interestingly, the analysis revealed that the future trendfi of CRM research would be based on techniques associated with machine learning and artificial intelligence. The study provides extensive insight into the basic structure of the CRM and data mining-based CRM research domain and identifies future research areas.

Development of Graphene-Based Materials in Bone Tissue Engineaering

Bone regeneration-related graphene-based materials (bGBMs) are increasingly attracting attention in tissue engineering due to their special physical and chemical properties. The purpose of this review is to quantitatively analyze mass academic literature in the field of bGBMs through scientometrics software CiteSpace, to demonstrate the rules and trends of bGBMs, thus to analyze and summarize the mechanisms behind the rules, and to provide clues for future research. First, the research status, hotspots, and frontiers of bGBMs are analyzed in an intuitively and vividly visualized way. Next, the extracted important subjects such as fabrication techniques, cytotoxicity, biodegradability, and osteoinductivity of bGBMs are presented, and the different mechanisms, in turn, are also discussed. Finally, photothermal therapy, which is considered an emerging area of application of bGBMs, is also presented. Based on this approach, this work finds that different studies report differing opinions on the biological properties of bGBMS due to the lack of consistency of GBMs preparation. Therefore, it is necessary to establish more standards in fabrication, characterization, and testing for bGBMs to further promote scientific progress and clinical translation.

Agricultural Eco-Efficiency: Challenges and Progress

The research on agricultural eco-efficiency has become an important point to deeply understand the interaction between ecological and environmental conditions and socio-economic factors as well as realize the coordinated development of agricultural economic development and environmental protection. (1) Background: This paper attempts to provide scientific support for the healthy and stable development of the agricultural economy and the sustainable development of ecological agriculture. (2) Methods: From a comprehensive perspective, this paper systematically analyze the overall situation, development trend, key fields, and hot fields of agricultural eco-efficiency in the past two decades. It consists of two complementary parts, including systematic quantitative literature review (based on CiteSpace) and traditional literature review. (3) Results: Agricultural eco-efficiency has evolved significantly with the popularization of agricultural machinery and the wide application of science and technology in the field of agricultural ecology. Its future development relies on the advances in our knowledge on theories and hypothesis, evaluation methods, impact on “socio-economic ecological” system, and drivers and regulation of agricultural eco-efficiency. For each of these fields, we find that challenges still exist. At present, the quantitative methods and index selection are not unified. We should deeply analyze the internal and external driving force of the development and change of ecological efficiency by constructing a complete theoretical framework for the research of agricultural ecological efficiency. At the same time, new technologies and methods are needed to evaluate agricultural eco-efficiency, and a balanced consensus between the improvement of agricultural eco-efficiency and the improvement of the ecological environment should be formed through empirical research.

Telemedicine in Arab Countries: Innovation, Research Trends, and Way Forward

Background: The progress and innovation in telemedicine within the Middle Eastern countries have not been heavily monitored. Therefore, the present study aims to analyze the scholarly work conducted in the Arab world, using reproducible statistical and scientometric techniques.

Methods: An electronic search of Web of Science (core database) had been conducted through use of an extensive search strategy comprising of keywords specific to the Arab region, EMRO countries, telehealth, medical conditions, and disorders. A total yield of 1,630 search results were processed, indexed through July 7, 2020. CiteSpace (5.7.R1, Drexel University, Pennsylvania, USA) is a Java-based application, a user-friendly tool for conducting scientometric analyses.

Results: The present analyses found a lack of innovation in the field of digital health in the Arab countries. Many gaps in research were found in Arab countries, which will be discussed subsequently. Digital health research was clustered around themes of big data and artificial intelligence; a lack of progress was seen in telemedicine and digital health. Furthermore, only a small proportion of these publications had principal or corresponding authors from Arab countries. A clear disparity in digital health research in the Arab world was evident after comparing these insights with our previous investigation on telemedicine research in the global context.

Conclusion: Telemedicine research is still in its infancy in the Middle Eastern countries. Recommendations include diversification of the research landscape and interdisciplinary collaborations in this area.

Global characteristics and trends of research on construction dust: based on bibliometric and visualized analysis

The booming construction industry has led to many environmental and occupational health and safety problems. Construction dust caused irreversible damage to the health of frontline workers and polluted the surrounding air environment, which has attracted the attention of researchers and practitioners. In this study, to systematically sort and analyze the distribution of construction dust (CD) research, its hot areas, and the evolution of its fronts, papers with "construction dust" as the subject term in the Web of Science Core Collection Database since 2010 are visually analyzed using CiteSpace. The characteristics of these papers, including the quantity trend, quality, author group, affiliated institution type, and journal type, are summarized, and keyword co-appearance and paper co-citation knowledge maps are produced. The results show that (1) China is the backbone of CD research, and the research results account for a considerable proportion of the total. (2) Respiratory dust and atmospheric aerosols, marble dust, PM_2.5, and other hot issues have always attracted international attention. And exposure assessment and spatial distribution were the main focuses in the study of CD. (3) The direction of CD research will explore in a more subtle and intelligent direction in the future, for example, monitoring and control equipment under the technical support of big data technology and machine learning and face recognition. By combining bibliometrics with a systematic review, we aim to analyze the research foci and future development direction deeply, providing scholars with a comprehensive view of the field.

Using Patent Technology Networks to Observe Neurocomputing Technology Hotspots and Development Trends

In recent years, development in the fields of big data and artificial intelligence has given rise to interest among scholars in neurocomputing-related applications. Neurocomputing has relatively widespread applications because it is a critical technology in numerous fields. However, most studies on neurocomputing have focused on improving related algorithms or application fields; they have failed to highlight the main technology hotspots and development trends from a comprehensive viewpoint. To fill the research gap, this study adopts a new viewpoint and employs technological fields as its main subject. Neurocomputing patents are subjected to network analysis to construct a neurocomputing technology hotspot. The results reveal that the neurocomputing technology hotspots are algorithms, methods or devices for reading or recognizing printed or written characters or patterns, and digital storage characterized by the use of particular electric or magnetic storage elements. Furthermore, the technology hotspots are discovered to not be clustered around particular fields but, rather, are multidisciplinary. The applications that combine neurocomputing with digital storage are currently undergoing the most extensive development. Finally, patentee analysis reveal that neurocomputing technology is mainly being developed by information technology corporations, thereby indicating the market development potential of neurocomputing technology. This study constructs a technology hotspot network model to elucidate the trend in development of neurocomputing technology, and the findings may serve as a reference for industries planning to promote emerging technologies.

A scientometric analysis of birth cohorts in South Asia: Way forward for Pakistan

The present study aims to: a) systematically map the of birth cohort studies from the South Asian region b) examine the major research foci and landmark contributions from these cohorts using reproducible scientometric techniques and c) offer recommendations on establishing new birth cohorts in Pakistan, building upon the strengths, weaknesses and gaps of previous cohorts. Bibliographic records for a total of 260 articles, published during through December 2018, were retrieved from the Web of Science (core database). All data were analysed using Microsoft Excel (2013), Web of Science platform and CiteSpace. A series of network analysis were then run for each time-period using the link reduction method and pathfinder network scaling. The co-cited articles were clustered into their homogeneous research clusters. The clusters were named using the Latent Semantic Indexing (LSI) method that utilized author keywords as source of names for these clusters. The scientometric analyses of original research output from these birth cohorts also paint a pessimistic landscape in Pakistan- where Pakistani sites for birth cohorts contributed only 31 publications; a majority of these utilized the MAL-ED birth cohort data. A majority of original studies were published from birth cohorts in India (156), Bangladesh (63), and Nepal (15). Out of these contributions, 31 studies reported data from multiple countries. The three major birth cohorts include prospective and multi-country MAL-ED birth cohort and The Pakistan Early Childhood Development Scale Up Trial, and a retrospective Maternal and infant nutrition intervention cohort. In addition to these, a few small-scale birth cohorts reported findings pertaining to neonatal sepsis, intrauterine growth retardation and its effects on linear growth of children and environmental enteropathy.

Outlining the keyword co-occurrence trends in Shuanghuanglian injection research: A bibliometric study using CiteSpace III

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Conclusion

Mapping the knowledge domain of road safety studies: A scientometric analysis

As a way of obtaining a visual expression of knowledge, mapping knowledge domain (MKD) provides a vision-based analytic approach to scientometric analysis which can be used to reveal an academic community, the structure of its networks, and the dynamic development of a discipline. This study, based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) articles on road safety, employs the bibliometric tools VOSviewer and CitNetExplorer to create maps of author co-citation, document co-citation, citation networks, analyze the core authors and classic documents supporting road safety studies and show the citation context and development of such studies. It shows that road safety studies clustered mainly into four groups, whose we will refer to as "effects of driving psychology and behavior on road safety", "causation, frequency and injury severity analysis of road crashes", "epidemiology, assessment and prevention of road traffic injury", and "effects of driver risk factors on driver performance and road safety", respectively. Through our analysis, the core publications and their citation relationships were quickly located and explored, and "crash frequency modeling analysis" has been identified to be the core research topic in road safety studies, with spatial statistical analysis technique emerging as a frontier of this topic.