Bibliometric Analysis of Trained Immunity in Inflammatory Bone Disease, 2013-2025

83 records form the core corpus for a bibliometric and text-mining analysis of trained immunity in inflammatory bone disease, with an extended corpus of 301 records. The dataset, created by Zihang Zhao and last updated in May 2026, analyzes publication trends from 2013 to 2025 using Web of Science Core Collection, Scopus, and PubMed. It includes topic modeling and semantic screening to map literature-level patterns connecting myeloid reprogramming and periodontitis.

Use Cases

• Analyze publication trends and growth in a niche research field based on the 2013-2025 comparison window.
• Perform semantic screening and topic modeling based on the TF-IDF and two-corpus design described.
• Map disease-context relationships and bridge networks based on the analysis linking concepts to conditions like periodontitis and osteoarthritis.
• Compare database coverage and record overlap based on the cross-database analysis of WoSCC, Scopus, and PubMed.

Strengths

• Includes a core corpus of 83 records and an extended corpus of 301 records for robust sensitivity analysis.
• Uses a multi-source approach with data from Web of Science Core Collection, Scopus, and PubMed for cross-validation.
• Applies multiple analytical methods including bibliometrics, topic modeling, TF-IDF screening, and network mapping.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale ML tasks.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small at 359.9 KB, indicating a limited scope focused on a specific literature review.

Provenance

Source

figshare

Collection Method

Bibliometric and literature-level text-mining analysis using Web of Science Core Collection as the primary source.

Time Range

2013-2025

Freshness

Last updated 2026-05-20 04:33:05; freshness should be verified.

Geography

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