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Purpose: This study aims to comprehensively assess the field of health informatics and its subdomains, addressing a gap in the literature. The primary objective is to provide insights into the integration of expertise from various disciplines and explore the impact of emerging technologies, such as artificial intelligence, machine learning, robotic process automation, and virtual reality on healthcare processes. The research question queries the current status of health informatics and how the latest technological developments affect health informatics and its subfields. Method: Conducted through an extensive literature review, this research explores medical informatics, nursing informatics, pharmacy informatics, dentistry informatics, biomedical informatics, bioinformatics, public health informatics, clinical informatics, and primary care informatics. Results: Findings highlight a comprehensive understanding of health informatics and its subdomains, emphasizing the interdisciplinary integration of expertise. The study also reveals the significant impact of new and hype technologies on various health informatics domains. Conclusions: Filling a literature gap, this study provides valuable insights into the current state of health informatics. It underscores the interdisciplinary nature of the field and emphasizes the profound influence of emerging technologies on the evolving landscape of health informatics. The study thoroughly examines nine specific informatics fields within health informatics, revealing that recent years have seen a collective influence of artificial intelligence, deep learning, and machine learning across these domainsThe findings strongly suggest that courses on these emerging current technologies be integrated into undergraduate curricula within health informatics education. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Turkish Court of Accounts / Sayistay Dergisi is the property of Turkish Court of Accounts and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: Bibliometrics, scientometrics and other related methodologies can be used to reveal the basic patterns, links to different subjects and areas, and demographic elements of a particular topic within the literature. The aim of this study is to reveal the patterns and trends in nursing research on hip fracture. Methods: This descriptive exploratory study can be classified in methodologies of bibliometrics, scientometrics and business intelligence. The Web of Science was the main data source. Related articles published between 1990 and 2020 were considered. In addition to tables, text analytics, and network models used in bibliometric mapping, Latent Dirichlet Allocation (LDA) enriched by business intelligence was utilized in the analysis of abstract data. Results: The total of 380 studies on hip fracture were identified (article=351, review=29). The number of retrieved articles exhibit an increasing trend by year, the highest number of articles was published in 2020. In terms of distribution of the 380 studies by country, the United States (n =159), Sweden (n =52) and Australia (n =32) were the top three countries. Among the ten topics identified by LDA, nursing care, mortality, and rehabilitation were the prominent ones. Nursing, delirium, and elderly were the most frequently used keywords. Frailty and rehabilitation were the most recently introduced keywords. Conclusion: The topics of nursing care, rehabilitation and care experiences have been studied intensively. Studies on issues that may occur with increasing age and where nursing care is important can be conducted in the future using business intelligence and bibliometric. [ABSTRACT FROM AUTHOR]

Copyright of Acta Paulista de Enfermagem is the property of Universidade Federal de Sao Paulo, Escola Paulista de Enfermagem and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to develop a pipeline for identifying and prioritising the processes to include in business process management (BPM) initiatives by considering the obstacles for giving equal importance to the processes performed in businesses. The paper proposes the use of a process classification framework as a reference for process identification and fuzzy multi‐criteria decision‐making methods for prioritising the processes. A real‐life application is presented, which adopts APQC Process Identification Framework, Fuzzy‐SWARA for weighting the criteria, and six additional methods for prioritising the processes. The approach would assist the executives in maintaining the BPM lifecycle by presenting a roadmap, especially for organisations that do not have much experience in this field. Methodological depth, richness and recency would provide guidelines for investigating the best set of processes to include in the architecture initially, not in the analysis or redesign phases. [ABSTRACT FROM AUTHOR]

Copyright of Journal of University Research / Üniversite Araştırmaları Dergisi is the property of Journal of University Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acta Infologica is the property of Acta Infologica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Verimlilik Dergisi is the property of Verimlilik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Kafkas University, Journal of Economics & Administrative Sciences Faculty / Kafkas Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of University of Kafkas, Faculty of Economics & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of University Research / Üniversite Araştırmaları Dergisi is the property of Journal of University Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Higher Education & Science / Yüksekögretim ve Bilim Dergisi is the property of Zonguldak Bulent Ecevit Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of University Research / Üniversite Araştırmaları Dergisi is the property of Journal of University Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study proposes a filtering approach based on text classification and a fuzzy multi-criteria decision-making technique to select the relevant bibliometric data for further analyses in the scope of bibliometrics, scientometrics, and related methodologies. The proposed approach is illustrated on Industry 4.0 and internet of things which are the concepts that currently draw utmost attention with a growing number of research and applications. Accordingly, various findings are presented revealing the characteristics of the selected bibliometric data with the help of text and network analytics. The potential contribution of this study is two-fold such that the study not only suggests a novel approach for clarifying the retrieved bibliometric data but also emphasises the mainstream research areas and directions of Industry 4.0 along with the concept of the internet of things. Thus, an analysis framework with computing techniques has been used to reveal the characteristics of literature in a field of technology. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Knowledge Economy & Knowledge Management is the property of Journal of Knowledge Economy & Knowledge Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Mehmet Akif Ersoy University Social Science Institute is the property of Mehmet Akif Ersoy University, Social Science Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Scientometrics, bibliometrics, webometrics, and informetrics are specific research fields that cover statistical analyses of a particular research field which summarize the information related to topics handled during a particular time period; authors, citations and their demographic characteristics; network relationships among the authors. This study, which can be classified in both scientometrics and webometrics, aims at revealing the current situation and the performance of academicians working in the nursing field in Turkey through basic and advanced data analyses conducted on their published original articles in a Web of Science. The raw data including the details of the publications were first parsed into a novel database where the authors’ affiliations were stored with respect to the data obtained from the website of the Turkish Higher Education Council. Over the integrated database, particular tables were generated to show the summary of the academic and demographic distributions of the publications. Specific statistical tests were applied to reveal the relationships and differences. Furthermore, analyses were carried out within text mining on authors, titles, keywords, abstracts, and references in order to examine the contents and references of the articles included in the data set to reveal keyword densities, particular topics, and co-authorship and citation networks. One of the challenging part of this research was the dataset collection and cleansing process, because of the special letters of Turkish Language, e.g. ç, ş, ö, ü. This issue was resolved when the representation pattern of the letters were discovered and queries were executed with respect to those patterns. This study has provided meaningful findings to both the field of nursing the scientometrics, since it reveals the academic performance in a particular field and systematically presents the current situation by examining the relevant studies in an analytical perspective. [ABSTRACT FROM AUTHOR]

Copyright of Dokuz Eylul University Muhendislik Faculty of Engineering Journal of Science & Engineering / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi is the property of Dokuz Eylul Universitesi Muhendislik Fakultesi Fen ve Muhendislik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Higher Education & Science / Yüksekögretim ve Bilim Dergisi is the property of Zonguldak Bulent Ecevit Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Higher Education & Science / Yüksekögretim ve Bilim Dergisi is the property of Zonguldak Bulent Ecevit Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article presents a novel application framework for the Network of the Universities from the Capitals of Europe based on business intelligence which is applied by analysing co-authorships through data from the Web of Science. It discusses that findings cover features of the monitoring environment and statistics in various research domains and provides an intellectual contribution by revealing the differences in collaboration levels of the research areas and indicating policy requirements.

Copyright of Dokuz Eylul University Journal of Graduate School of Social Sciences is the property of Dokuz Eylul University Graduate School of Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)