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Global trends and characteristics of metal–organic frameworks in cancer research: a machine-learning-based bibliometric analysis

3Citations signalées — pas une note de qualité
2Institutions déclarées
1Pays d’affiliation déclarés

Résumé fourni par la source

BACKGROUND: Cancer poses a significant health threat, causing millions of deaths annually. Although chemotherapy-based comprehensive therapies are common, their low accuracy and severe side effects limit effectiveness. Metal-organic frameworks (MOFs), with their superior biocompatibility and stability, show great promise for drug delivery and cancer treatment. This study aims to explore the potential and developmental trajectories of MOFs in cancer research through a bibliometric analysis. METHODS: The Web of Science Core Collection was searched for documents from its inception in 2009 to December 31, 2023. We analyzed and visualized document types, countries, institutions, authors, journals, references, and keywords using the Bibliometrix package, dplyr, sankeywheel, term extraction, and ggplot2. Additionally, the Latent Dirichlet Allocation (LDA) algorithm was employed for detailed semantic analysis, uncovering latent thematic distributions. RESULTS: A total of 7106 authors from 1591 institutions across 45 countries contributed 1955 papers on MOFs in cancer research, published in 327 journals. China leads in research output and international collaboration, with the Chinese Academy of Sciences as the top institution. Lin Wenbin from the University of Chicago is the most influential author, and ACS Applied Materials & Interfaces is the most active journal. MOFs are predominantly studied for breast cancer, followed by lung and liver cancers. Drug delivery remains a focal point for future research. CONCLUSIONS: This study provides a comprehensive overview of the research landscape on MOFs in cancer treatment, offering insights into key trends and future directions, particularly in drug delivery and disease-specific applications.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Global trends and characteristics of metal–organic frameworks in cancer research: a machine-learning-based bibliometric analysis
Date Crossref
01/06/2025
Éditeur
Springer Science and Business Media LLC
Type
journal-article

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Institutions déclarées

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Sujets associés

Metal-Organic Frameworks: Synthesis and ApplicationsDendrimers and Hyperbranched PolymersComputational Drug Discovery Methods

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