| Literature DB >> 35154009 |
Zeyu Zhang1, Fada Xia1, Xinying Li1.
Abstract
Introduction: Parathyroid tumor, in particular carcinoma, is fairly rare among neoplasms of the endocrine system, unlike its benign counterpart. However, there is no bibliometric analysis in the field of parathyroid tumors comprehensively summarizing and discussing a large number of publications by a machine learning-based method. Materials andEntities:
Keywords: bibliometrics; machine learning; natural language processing; parathyroid tumor; parathyroidectomy
Mesh:
Substances:
Year: 2022 PMID: 35154009 PMCID: PMC8826231 DOI: 10.3389/fendo.2021.811555
Source DB: PubMed Journal: Front Endocrinol (Lausanne) ISSN: 1664-2392 Impact factor: 5.555
Figure 1Scientific publications per year.
Figure 2Distribution of publication types per year.
Figure 3Country scientific production.
Top 10 affiliations with the highest scientific production.
| Name of affiliation | Number of articles |
|---|---|
| The University of Texas MD Anderson Cancer Center | 94 |
| Peking Union Medical College Hospital | 94 |
| University of Pisa | 57 |
| University of Connecticut School of Medicine | 50 |
| University of Wisconsin | 50 |
| Duke University Medical Center | 49 |
| Postgraduate Institute of Medical Education & Research (PGIMER) | 48 |
| Capital Medical University | 46 |
| Centre Hospitalier Universitaire De Nantes | 44 |
| University Of Milan | 43 |
Top three terms in general study issues of parathyroid tumor during the past 20 years.
| Category | Name of affiliation | Number of occurrences |
|---|---|---|
| Study subject | Human | 3,264 |
| Animal | 91 | |
| Cell | 15 | |
| Age group | Middle aged | 1,651 |
| Adult | 1,292 | |
| Aged | 1,157 | |
| Study design | Retrospective studies | 509 |
| Follow-up studies | 208 | |
| Prospective studies | 138 |
Figure 4(A) Accumulative occurrences of top 8 MeSH terms concerning the diagnosis of parathyroid tumor. (B) Accumulative occurrences of top 8 MeSH terms concerning the treatment of parathyroid tumor.
Figure 5Topic cluster network by Latent Dirichlet Allocation. Green, Diagnosis research; Purple, Treatment research; Red, Basic research. The size of the circle represents the number of papers in each topic, and the thickness of the line represents the weight of the connection between each topic.