Background: Bibliometric analysis is a quantitative tool to evaluate collaboration and the impact of publications within a given field. This study aims to elucidate the methodologies used in different databases for bibliometric analysis, offering a detailed comparison of their pros and cons. Methods: PubMed, Scopus, Web of Science (WOS), and Lens were used in this comparative study, with search examples of the “University of Jordan” in the period (2019-2023). 2739, 7777, 7518, and 4326 publications were retrieved from these databases, respectively. PubMed has the least number of documents due to its limited scope. Microsoft Excel 2019 and VOSviewer 1.6.20 were used to assess the data analysis. Results: Annual growth was observed across all databases, except for Lens database. The majority of top authors were found to be shared among different databases, with variations in the number of documents, and WOS had the least number of documents per author. The top countries were shared between Scopus and WOS, but there was a substantial difference in the number of citations between WOS and Scopus. In institutions analysis, most were ranked as institute with their department, except in WOS where the results were reported as generalizable to the institute level. Keyword analysis revealed a significant similarity between different databases. Journals distribution also had a great similarity across different databases and variable documents. Conclusion: Researchers should choose a bibliographic database based on their specific needs, considering factors like coverage and accessibility. This study provides a comparative analysis of various databases, including the Lens database.

Background: Cardiovascular diseases (CVDs) remain the leading cause of mortality, especially in low‐ and middle‐income countries, many of which are in the Arab region. We aimed to conduct a bibliometric analysis to assess the scientific output concerning CVDs in the Arab region and the Middle East over the past decade.Methods: A bibliometric search was conducted on PubMed and Scopus between 2012 and 2022. The study analyzed the number of publications, countries, institutional sources, authors, journals, and keywords. Visualization analysis was executed using various software tools, including R, VOSviewer, and CiteSpace.Results: PubMed and Scopus yielded 5340 documents related to CVDs at the time of data collection. A total of 1263 documents were retrieved after screening based on specific inclusion criteria that guarantee the inclusion only for Arab region studies and authors. There has been a consistent increase in annual publications in recent years. The countries that contributed the most to research in this field were Egypt, Saudi Arabia, and the UAE. Although Egypt stood out as the most productive country, the institute with the highest number of documents was in Qatar. In addition, the Top 3 authors hailed from Qatar. Saudi Medical Journal leads the field as the most productive journal, followed closely by PLoS One and Angiology. Research topics of significant interest in the realm of CVDs include specific diseases such as heart failure, risk factors related to CVDs, genetic aspects of CVDs, and congenital disorders in infant’s cardiac health.Conclusion: This study provides a comprehensive overview of the current status of CVD research in the Arab region. It includes research hotspots that can guide authors in determining the necessary future investigations within this field. There is a clear call for further exploration of various aspects of CVDs in the Arab world. Strengthening cooperation between countries and institutes is needed.

Total knee arthroplasty (TKA) is a widely performed procedure that significantly enhances patients’ quality of life by reducing pain and improving daily function. While the traditional tibial plate design used in TKA has been symmetrical, there has been a recent trend towards using asymmetrical designs. Our study aimed to compare symmetrical and asymmetrical tibial designs, focusing on outcomes related to overhang, malrotation, and tibial coverage. This systematic review was conducted in accordance with PRISMA guidelines. A comprehensive search of PubMed, Scopus, Web of Science, and Cochrane databases was carried out up to January 22nd, 2024, to identify comparative studies on symmetrical and asymmetrical designs, as well as those reporting postoperative functional and clinical outcomes. The risk of bias in the included studies was evaluated using the Newcastle-Ottawa Scale (NOS). This systematic review included 587 patients from seven comparative studies that met the inclusion criteria. Our findings indicate that asymmetrical tibial components generally provided better outcomes in terms of tibial coverage, malrotation, and overhang. Asymmetrical designs provided greater tibial coverage and reduced posterolateral overhang compared to symmetrical designs, which is essential for minimizing complications like soft tissue irritation and patellar maltracking. Additionally, asymmetrical components were associated with less severe tibial malrotation. This systematic review showed that asymmetrical tibial implants offer better tibial coverage, with less overhang and fewer rotational issues compared to symmetrical implants. As a result, asymmetrical designs in TKA may lower complication rates, enhance patient satisfaction, and improve quality of life post-surgery.

BACKGROUND Artificial intelligence (AI) has become significantly integrated into healthcare, particularly in the diagnosing of neurological disorders. This advancement has enabled neurologists and physicians to diagnose conditions more quickly and effectively, ultimately benefiting patients. AIM To explore the current status and key highlights of AI-related articles in diagnosing of neurological disorders. METHODS A systematic literature review was conducted in the Web of Science Core Collection database using the following strategy: TS = ("Artificial Intelligence" OR "Computational Intelligence" OR "Machine Learning" OR "AI") AND TS = ("Neurological disorders" OR "CNS disorder" AND "diagnosis"). The search was limited to articles and reviews. Microsoft Excel 2019 and VOSviewer were utilized to identify major contributors, including authors, institutions, countries, and journals. Additionally, VOSviewer was employed to analyze and visualize current trends and hot topics through network visualization maps. RESULTS A total of 276 publications from 2000 to 2024 were retrieved. The United States, India, and China emerged as the top contributors in this field. Major institutions included Johns Hopkins University, King's College London, and Harvard Medical School. The most prolific author was U. Rajendra Acharya from the University of Southern Queensland (Australia). Among journals, IEEE Access , Scientific Reports , and Sensors were the most productive, while Frontiers in Neuroscience led in total citations. Central topics in AI-related articles on neurological disorders diagnosis included Alzheimer's disease, Parkinson's disease, dementia, epilepsy, autism, attention deficit hyperactivity disorder, and their intersections with deep learning and AI. CONCLUSION Research on AI's role in diagnosing neurological disorders is becoming widely recognized for its growing importance. AI shows promise in diagnosing various neurological disorders, yet requires further improvement and extensive future research.

Background and objectives: Tuberculosis (TB) is one of the leading causes of death from infectious diseases worldwide with numerous undiagnosed and untreated cases, emphasizing the need for TB awareness to minimize transmission and initiate early treatment. Data regarding the knowledge,...