Bibliometric Analysis of Scientific Output and Collaboration Patterns at West Kazakhstan Marat Ospanov Medical University

2026

Full text Open access: Hybrid Metadata (CSL-JSON)
DOI 10.4103/wkbj.wkbj_23_26
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

A BSTRACT Background: Bibliometric analysis provides a quantitative approach to evaluate research productivity, collaboration patterns, and scientific impact. Assessing institutional performance using such methods is essential for understanding research development and guiding strategic planning. Objective: This study aimed to analyze the scientific output, collaboration networks, and journal impact of publications affiliated with West Kazakhstan Marat Ospanov Medical University (WKMU) from 2010 to 2026. Materials and Methods: A bibliometric analysis was conducted using data retrieved from the Scopus database. Publications affiliated with WKMU were identified and exported in CSV format. Data preprocessing and analysis were performed using Python, including normalization of journal names, author parsing, and ISSN standardization. Journal impact was assessed using Web of Science quartile rankings (Q1–Q4), which were integrated through matching by ISSN and journal title. Bibliometric indicators included annual publication output, author productivity, quartile distribution, and international collaboration patterns. Visualization techniques such as bar charts, bubble plots, and network graphs were employed. Results: A total of 602 publications were analyzed. Scientific output increased substantially after 2020, with a notable rise in Q1 publications, peaking in 2025. Most publications were concentrated in Q2 journals, although Q1 output showed significant growth in recent years. A small group of authors contributed disproportionately to both total and Q1 publications. International collaboration was centered on Kazakhstan, with strong links to Russia, Iran, Poland, and the United States. Conclusion: WKMU demonstrates a growing research profile, with increasing productivity and a shift toward higher-impact journals. Strengthening international collaboration and supporting high-performing researchers may further enhance institutional research visibility and impact.