ArticleTranslational cancer research2026
Temporal-spatial evolution of tumor habitat analysis: a bibliometric study on research hotspots and trends in medical imaging (2014-2025).
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
11 authors.
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Abstract
Background: Tumor habitat analysis holds significant application potential in oncology, yet systematic bibliometric studies to characterize its research landscape remain limited. This study aims to comprehensively assess the current status, hotspots, and trends in this field using rigorous bibliometric methods, providing a theoretical framework for future research. Methods: English publications on medical imaging applications in tumor habitat analysis indexed in Web of Science Core Collection (WOSCC) and PubMed (inception to April 2025) were retrieved. VOSviewer and CiteSpace were used to visualize and analyze country/region contributions, authors, journals, references, and keyword co-occurrences. Results: A final set of 127 studies was included, revealing a rapid acceleration in research; annual output grew from a single article in 2014 to a peak of 36 in 2024, with 30 articles already published by April 2025. China was the most productive country, while the United States anchored the densest international collaboration network. Key contributors included the University of Ulsan, the journal Conclusions: Tumor habitat analysis research is growing rapidly, but methodological standardization and data integration remain critical challenges. Addressing these gaps will enhance result comparability and advance translational oncology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.