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Updated: Sep 27, 2026
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
Brain Health Research in PubMed/MEDLINE: A Bibliometric Analysis of Thematic Structure and Health-Economic
Ioannis Ch Lampropoulos1, Georgia Xiromerisiou2,3
1Department of Business Administration, University of Patras, 26504 Patras, Greece.
Background/Objectives:
Brain health is an interdisciplinary field; however, the prominence of health-economic concepts within the PubMed/MEDLINE literature explicitly retrieved using the term 'brain health' has not been systematically characterized. The present study aimed to map the scientific landscape of the retrieved brain health literature and to examine the representation and network prominence of health-economic concepts within this corpus.
Methods:
Two separate PubMed/MEDLINE searches were conducted using the exact search expression "brain health". The overall search was performed on 8 April 2026 and yielded an analytical corpus of 18,306 publications (1993-2026), while a separate search on 9 May 2026, restricted by publication year to 2023-2026, yielded the recent-period analytical corpus (n = 10,908). Bibliometric analyses were performed using VOSviewer (version 1.6.20), including keyword co-occurrence analysis and thesaurus-based term standardization.
Results:
The overall keyword co-occurrence analysis identified five principal thematic clusters: neurobiological mechanisms (n = 117 items), public health and lifestyle (n = 67), neurodegeneration and biomarkers (n = 54), neuroimaging and vascular factors (n = 37), and neurophysiology and interventions (n = 25). The independently retrieved recent-period corpus showed a seven-cluster thematic structure, with prominent topics including neuroinflammation, blood-based biomarkers, and machine-learning applications. The targeted analysis identified health-economic concepts in the complete dataset, including cost-benefit analysis (n = 37), cost of illness (n = 28), cost-effectiveness (n = 24), and healthcare costs (n = 21), but these concepts showed relatively low frequency and limited prominence in the principal co-occurrence network. These findings indicate that health-economic concepts are present within the analyzed PubMed/MEDLINE corpus but show relatively low frequency and limited prominence in the principal keyword co-occurrence network.
Conclusions:
Within the PubMed/MEDLINE corpus analyzed, health-economic concepts showed relatively low frequency and limited prominence in the principal keyword co-occurrence network. Because the analysis was restricted to PubMed/MEDLINE and used the exact search expression 'brain health', these findings characterize the retrieved corpus and should not be interpreted as evidence of a general disconnect between brain health and health economics across the broader multidisciplinary literature. Informed by the bibliometric findings and the broader literature discussed in the manuscript, a conceptual three-axis framework is subsequently proposed, comprising: (1) disease-cost assessment, (2) economic evaluation and return-on-investment assessment of preventive interventions, and (3) population-level brain health performance indicators.
