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Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
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Global Suicide Mortality Rates (2000-2019): Clustering, Themes, and Causes Analyzed through Machine Learning and

Erinija Pranckeviciene1,2, Judita Kasperiuniene1,3

  • 1Faculty of Informatics, Vytautas Magnus University, LT-53361 Akademija Kauno r., Lithuania.

International Journal of Environmental Research and Public Health
|September 28, 2024
PubMed
Summary

Global suicide mortality rates (SMRs) vary significantly. This study groups countries by SMR trends and analyzes research themes, revealing distinct regional patterns in suicide research and its causes.

Keywords:
age-adjusted suicide mortality rateassociation rule miningbibliographic analysiskeyword clusteringmachine learningnetwork analysisrecurrent neural networksuicidetext miningword embedding

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Area of Science:

  • Public Health
  • Epidemiology
  • Sociology

Background:

  • Significant disparities exist in global suicide mortality rates (SMRs).
  • The World Health Organization (WHO) and Web of Science (WoS) database offer valuable data on SMRs and suicide research.
  • Understanding these disparities requires analyzing both mortality data and research trends.

Purpose of the Study:

  • To analyze global suicide mortality rates (SMRs) and identify distinct country groupings based on SMR trends.
  • To explore the thematic landscape of suicide research worldwide and within specific regions.
  • To investigate the relationship between SMRs and research themes using bibliometric analysis.

Main Methods:

  • Hierarchical clustering of age-standardized SMRs (2000-2019).
  • Network and association rule mining of country-specific suicide publication keywords from WoS.
  • Recurrent neural network for keyword embedding.

Main Results:

  • Countries naturally segregated into high, medium, and low SMR groups.
  • Worldwide suicide research themes include depression, youth suicide, and substance abuse.
  • Region-specific themes identified: alcohol (post-Soviet), HIV/AIDS (Sub-Saharan Africa), PTSD (Middle East), and student suicide (East Asia).

Conclusions:

  • Global SMRs form distinct clusters characterized by unique research themes.
  • The methodology allows for integrating bibliometric data to interpret complex SMR patterns.
  • This approach enhances the understanding of socio-economic and regional factors influencing suicide.