ArticleFrontiers in oncology2022
A Bibliometric Analysis of the Landscape of Parathyroid Carcinoma Research Based on the PubMed (2000-2021).
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Applications of Natural Language Processing in Otolaryngology: A Scoping Review.The Laryngoscope · 2025Article
- Machine Learning-based Analysis of Publications Funded by the National Institutes of Health's Initial COVID-19 Pandemic Response.Open forum infectious diseases · 2024Article
- A bibliometric analysis based on Web of Science from 2012 to 2021: Current situation, hot spots, and global trends of medullary thyroid carcinoma.Frontiers in oncology · 2023Article
- Exploring changes in depression and radiology-related publications research focus: A bibliometrics and content analysis based on natural language processing.Frontiers in psychiatry · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe purpose of this study was to assess the landscape of parathyroid carcinoma research during the last 22 years using machine learning and text analysis.
methodIn November 2021, we obtained from PubMed all works indexed under the mesh subject line "parathyroid carcinoma". The entire set of search results was retrieved in XML format, and metadata such as title, abstract, keywords, mesh words, and year of publication were extracted for bibliometric evaluation from the original XML files. To increase the specificity of the investigation, the Latent Dirichlet allocation (LDA) topic modeling method was applied.
resultsThe paper analyzed 3578 papers. The volume of literature related to parathyroid cancer has been relatively flat over the past 22 years. In the field of parathyroid cancer research, the most important topic of clinical interest is the differential diagnosis. Ultrasound and MIBI are the most commonly used imaging methods for localization. In terms of basic research, the mechanisms of gene mutation and local tumor recurrence are the focus of interest.
conclusionThere are huge unmet research needs for parathyroid carcinoma. Improving the diagnosis rates of parathyroid cancer by clinicians and establishing new and reliable molecular pathological markers and new image localization techniques will continue to be the focus of future research.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.