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A bibliometric analysis of studies on Parkinson’s disease (PD) listed on the institutional website of the Michael J. Fox Foundation (MJFF) from 2003 to 2024 was conducted. PD is a neurodegenerative condition of the central nervous system that causes motor and non-motor dysfunction and affects 1% of the population over 60 years old. The MJFF has been instrumental in accelerating the development of treatments, funding relevant projects, and providing essential data for PD research. This study utilized metadata from 7370 articles, from which data were extracted using web scraping techniques and APIs such as National Center for Biotechnology Information (NCBI) Entrez Metadata from 6,923 articles were retrieved, and the results were processed using R and Python language for bibliometric analysis and visualization. The research highlights the significant role of MJFF in PD research and provides insights into the trends and focuses of foundation supported research. This study not only contributes to a better understanding of the PD field but also exemplifies the application of bibliometric techniques to assess the evolution of research in a specific area.

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A Bibliometric Study on Parkinson’s Disease Based on the Open Access Data of the Michael J. Fox Foundation

  • 会议论文

  • 发表日期：

    2025年

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  • Leandro Rodrigues da Silva Sousa,
  • Daniel Hilário da Silva,
  • Caio Tonus Ribeiro,
  • Pedro Henrique Bernardes Caetano Milken,
  • Slawomir J. Nasuto,
  • Catherine M. Sweeney-Reed,
  • Adriano de Oliveira Andrade,
  • Adriano Alves Pereira

摘要

A bibliometric analysis of studies on Parkinson’s disease (PD) listed on the institutional website of the Michael J. Fox Foundation (MJFF) from 2003 to 2024 was conducted. PD is a neurodegenerative condition of the central nervous system that causes motor and non-motor dysfunction and affects 1% of the population over 60 years old. The MJFF has been instrumental in accelerating the development of treatments, funding relevant projects, and providing essential data for PD research. This study utilized metadata from 7370 articles, from which data were extracted using web scraping techniques and APIs such as National Center for Biotechnology Information (NCBI) Entrez Metadata from 6,923 articles were retrieved, and the results were processed using R and Python language for bibliometric analysis and visualization. The research highlights the significant role of MJFF in PD research and provides insights into the trends and focuses of foundation supported research. This study not only contributes to a better understanding of the PD field but also exemplifies the application of bibliometric techniques to assess the evolution of research in a specific area.