Analysis of research trends in Korean dentistry journals by assigning MeSH to author keywords

Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings. We investigated research trends by selecting high-frequency words from author keywords (AKs), analyzing subject areas, and performing quantit...

Full description

Saved in:
Bibliographic Details
Published inMedicine (Baltimore) Vol. 99; no. 38; p. e22190
Main Authors Jeong, Sona, Jeong, Ji Na
Format Journal Article
LanguageEnglish
Published United States Lippincott Williams & Wilkins 18.09.2020
Subjects
Online AccessGet full text
ISSN0025-7974
1536-5964
1536-5964
DOI10.1097/MD.0000000000022190

Cover

Abstract Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings. We investigated research trends by selecting high-frequency words from author keywords (AKs), analyzing subject areas, and performing quantitative data analysis of Korean dental journals. Consequently, we suggest a method for choosing journals that fit a specific subject area.We used a corpus of 9 Korean dentistry journals regarded in Korea as quality internationally approved journals. AKs occurring more than 10 times were assigned to Medical Subject Headings (MeSH) terms and subcategories, which were then categorized using the MeSH tree structure. KnowledgeMatrix Plus and VOSviewer were used to analyze network relationships, density, and clustering.The AKs were of 7527 types, 15,960 terms, and formed 54 clusters. The AKs with 10+ occurrence were 199 types, 4289 terms, and formed 9 clusters. Assigning the AKs with 10+ occurrence to MeSH terms led to expanding 732 types of AK terms into 249 types with 9 clusters and 4268 links. Core study areas over the past 10 years were facial asymmetry, a topic under oral surgery and medicine, and orthognathic surgery focused on mandibular fractures, followed by shear bond strength of zirconia. Analyzing 16 MeSH subject categories, we found that the "analytical, diagnostic and therapeutic techniques and equipment" category had the largest distribution of AKs (40.7%). This was followed by "diseases" (21.2%) and "anatomy" (14.90%). The orthognathic surgery cluster was the largest, followed by the shear bond strength cluster. Dental implants is a core area with strong links to high-occurrence words, such as cone-beam computed tomography and mandible, which were distributed in the order of The Journal of Advanced Prosthodontics (37.8%) and Journal of Periodontal & Implant Science (30.6%). Five clusters were closely packed in the center, 2 clusters were formed above the center, 1 cluster was formed below the center, and a cluster on the right was widespread.Cluster analysis using AKs and MeSH may be a good analytic method for researchers to determine expanding research areas and select optimal journals for paper submission.
AbstractList Supplemental Digital Content is available in the text Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings. We investigated research trends by selecting high-frequency words from author keywords (AKs), analyzing subject areas, and performing quantitative data analysis of Korean dental journals. Consequently, we suggest a method for choosing journals that fit a specific subject area. We used a corpus of 9 Korean dentistry journals regarded in Korea as quality internationally approved journals. AKs occurring more than 10 times were assigned to Medical Subject Headings (MeSH) terms and subcategories, which were then categorized using the MeSH tree structure. KnowledgeMatrix Plus and VOSviewer were used to analyze network relationships, density, and clustering. The AKs were of 7527 types, 15,960 terms, and formed 54 clusters. The AKs with 10+ occurrence were 199 types, 4289 terms, and formed 9 clusters. Assigning the AKs with 10+ occurrence to MeSH terms led to expanding 732 types of AK terms into 249 types with 9 clusters and 4268 links. Core study areas over the past 10 years were facial asymmetry, a topic under oral surgery and medicine, and orthognathic surgery focused on mandibular fractures, followed by shear bond strength of zirconia. Analyzing 16 MeSH subject categories, we found that the “analytical, diagnostic and therapeutic techniques and equipment” category had the largest distribution of AKs (40.7%). This was followed by “diseases” (21.2%) and “anatomy” (14.90%). The orthognathic surgery cluster was the largest, followed by the shear bond strength cluster. Dental implants is a core area with strong links to high-occurrence words, such as cone-beam computed tomography and mandible, which were distributed in the order of The Journal of Advanced Prosthodontics (37.8%) and Journal of Periodontal & Implant Science (30.6%). Five clusters were closely packed in the center, 2 clusters were formed above the center, 1 cluster was formed below the center, and a cluster on the right was widespread. Cluster analysis using AKs and MeSH may be a good analytic method for researchers to determine expanding research areas and select optimal journals for paper submission.
Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings. We investigated research trends by selecting high-frequency words from author keywords (AKs), analyzing subject areas, and performing quantitative data analysis of Korean dental journals. Consequently, we suggest a method for choosing journals that fit a specific subject area.We used a corpus of 9 Korean dentistry journals regarded in Korea as quality internationally approved journals. AKs occurring more than 10 times were assigned to Medical Subject Headings (MeSH) terms and subcategories, which were then categorized using the MeSH tree structure. KnowledgeMatrix Plus and VOSviewer were used to analyze network relationships, density, and clustering.The AKs were of 7527 types, 15,960 terms, and formed 54 clusters. The AKs with 10+ occurrence were 199 types, 4289 terms, and formed 9 clusters. Assigning the AKs with 10+ occurrence to MeSH terms led to expanding 732 types of AK terms into 249 types with 9 clusters and 4268 links. Core study areas over the past 10 years were facial asymmetry, a topic under oral surgery and medicine, and orthognathic surgery focused on mandibular fractures, followed by shear bond strength of zirconia. Analyzing 16 MeSH subject categories, we found that the "analytical, diagnostic and therapeutic techniques and equipment" category had the largest distribution of AKs (40.7%). This was followed by "diseases" (21.2%) and "anatomy" (14.90%). The orthognathic surgery cluster was the largest, followed by the shear bond strength cluster. Dental implants is a core area with strong links to high-occurrence words, such as cone-beam computed tomography and mandible, which were distributed in the order of The Journal of Advanced Prosthodontics (37.8%) and Journal of Periodontal & Implant Science (30.6%). Five clusters were closely packed in the center, 2 clusters were formed above the center, 1 cluster was formed below the center, and a cluster on the right was widespread.Cluster analysis using AKs and MeSH may be a good analytic method for researchers to determine expanding research areas and select optimal journals for paper submission.Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings. We investigated research trends by selecting high-frequency words from author keywords (AKs), analyzing subject areas, and performing quantitative data analysis of Korean dental journals. Consequently, we suggest a method for choosing journals that fit a specific subject area.We used a corpus of 9 Korean dentistry journals regarded in Korea as quality internationally approved journals. AKs occurring more than 10 times were assigned to Medical Subject Headings (MeSH) terms and subcategories, which were then categorized using the MeSH tree structure. KnowledgeMatrix Plus and VOSviewer were used to analyze network relationships, density, and clustering.The AKs were of 7527 types, 15,960 terms, and formed 54 clusters. The AKs with 10+ occurrence were 199 types, 4289 terms, and formed 9 clusters. Assigning the AKs with 10+ occurrence to MeSH terms led to expanding 732 types of AK terms into 249 types with 9 clusters and 4268 links. Core study areas over the past 10 years were facial asymmetry, a topic under oral surgery and medicine, and orthognathic surgery focused on mandibular fractures, followed by shear bond strength of zirconia. Analyzing 16 MeSH subject categories, we found that the "analytical, diagnostic and therapeutic techniques and equipment" category had the largest distribution of AKs (40.7%). This was followed by "diseases" (21.2%) and "anatomy" (14.90%). The orthognathic surgery cluster was the largest, followed by the shear bond strength cluster. Dental implants is a core area with strong links to high-occurrence words, such as cone-beam computed tomography and mandible, which were distributed in the order of The Journal of Advanced Prosthodontics (37.8%) and Journal of Periodontal & Implant Science (30.6%). Five clusters were closely packed in the center, 2 clusters were formed above the center, 1 cluster was formed below the center, and a cluster on the right was widespread.Cluster analysis using AKs and MeSH may be a good analytic method for researchers to determine expanding research areas and select optimal journals for paper submission.
Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings. We investigated research trends by selecting high-frequency words from author keywords (AKs), analyzing subject areas, and performing quantitative data analysis of Korean dental journals. Consequently, we suggest a method for choosing journals that fit a specific subject area.We used a corpus of 9 Korean dentistry journals regarded in Korea as quality internationally approved journals. AKs occurring more than 10 times were assigned to Medical Subject Headings (MeSH) terms and subcategories, which were then categorized using the MeSH tree structure. KnowledgeMatrix Plus and VOSviewer were used to analyze network relationships, density, and clustering.The AKs were of 7527 types, 15,960 terms, and formed 54 clusters. The AKs with 10+ occurrence were 199 types, 4289 terms, and formed 9 clusters. Assigning the AKs with 10+ occurrence to MeSH terms led to expanding 732 types of AK terms into 249 types with 9 clusters and 4268 links. Core study areas over the past 10 years were facial asymmetry, a topic under oral surgery and medicine, and orthognathic surgery focused on mandibular fractures, followed by shear bond strength of zirconia. Analyzing 16 MeSH subject categories, we found that the "analytical, diagnostic and therapeutic techniques and equipment" category had the largest distribution of AKs (40.7%). This was followed by "diseases" (21.2%) and "anatomy" (14.90%). The orthognathic surgery cluster was the largest, followed by the shear bond strength cluster. Dental implants is a core area with strong links to high-occurrence words, such as cone-beam computed tomography and mandible, which were distributed in the order of The Journal of Advanced Prosthodontics (37.8%) and Journal of Periodontal & Implant Science (30.6%). Five clusters were closely packed in the center, 2 clusters were formed above the center, 1 cluster was formed below the center, and a cluster on the right was widespread.Cluster analysis using AKs and MeSH may be a good analytic method for researchers to determine expanding research areas and select optimal journals for paper submission.
Author Jeong, Sona
Jeong, Ji Na
AuthorAffiliation Department of Health Management, Jeonju University, Jeonju, Korea
AuthorAffiliation_xml – name: Department of Health Management, Jeonju University, Jeonju, Korea
– name: a Department of Library & Information Science, Sookmyung Women's University
– name: c Department of Health Management, Jeonju University, Jeonju, Korea
– name: b Medical Library, the Catholic University of Korea, Seoul
Author_xml – sequence: 1
  givenname: Sona
  surname: Jeong
  fullname: Jeong, Sona
  organization: Department of Library & Information Science, Sookmyung Women's University
– sequence: 2
  givenname: Ji Na
  surname: Jeong
  fullname: Jeong, Ji Na
  organization: Department of Health Management, Jeonju University, Jeonju, Korea
BackLink https://www.ncbi.nlm.nih.gov/pubmed/32957346$$D View this record in MEDLINE/PubMed
BookMark eNqFkU1vFDEMhiNURLeFX4CEcuQyxfma2VyQqrZQRFccgCOKsjOenbSzSUkyrObfk7KlQC_4Ysl-3teWfUQOfPBIyEsGJwx082Z1fgJ_gnOm4QlZMCXqSulaHpBFqaqq0Y08JEcpXQMw0XD5jBwKrlUjZL0g3069HefkEg09jZjQxnagOaLvEnWefgwRracd-uxSjjO9DlMskkTXM7UpuY13fkNX-PmS5kDtlIcQ6Q3OuxC79Jw87QuLL-7zMfn67uLL2WV19en9h7PTq6qVCkSlJKpGLxXItQXLrG46lMDamtWAnFlgFrs1oCpd3mnOesQlU7KXWkKDvTgmb_e-t9N6i11bto12NLfRbW2cTbDO_NvxbjCb8MM0CpSQqhi8vjeI4fuEKZutSy2Oo_UYpmS4lHLZiKWUBX3196yHIb9vWgCxB9oYUorYPyAMzN3nzOrcPP5cUelHqtZlm124W9iN_9HKvXYXxowx3YzTDqMZ0I55-IWX8_KKAwfQbAlVqUghfgKT5K1N
CitedBy_id crossref_primary_10_1111_cid_13024
crossref_primary_10_1016_j_ctim_2024_103099
Cites_doi 10.11607/jomi.6727
10.1097/MD.0000000000016782
10.3389/fphar.2019.00564
10.1007/s11192-009-0146-3
10.4103/ijpvm.IJPVM_346_18
10.1371/journal.pone.0201435
10.1016/j.socnet.2004.11.008
10.1016/j.clineuro.2020.105740
10.3390/ijerph15102181
10.5125/jkaoms.2019.45.4.186
10.3346/jkms.2017.32.2.173
10.1186/s40545-018-0133-2
10.1093/femsle/fnz004
10.1371/journal.pone.0119503
10.2196/15142
10.1177/0193841X9401800110
10.11607/jomi.5331
ContentType Journal Article
Copyright Lippincott Williams & Wilkins
Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. 2020
Copyright_xml – notice: Lippincott Williams & Wilkins
– notice: Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. 2020
DBID AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7X8
5PM
DOI 10.1097/MD.0000000000022190
DatabaseName CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
MEDLINE - Academic
PubMed Central (Full Participant titles)
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
MEDLINE - Academic
DatabaseTitleList
MEDLINE - Academic
MEDLINE
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Dentistry
EISSN 1536-5964
EndPage e22190
ExternalDocumentID PMC7505345
32957346
10_1097_MD_0000000000022190
00005792-202009180-00043
Genre Journal Article
GeographicLocations Republic of Korea
GeographicLocations_xml – name: Republic of Korea
GroupedDBID ---
.-D
.XZ
.Z2
01R
0R~
354
40H
4Q1
4Q2
4Q3
5GY
5RE
5VS
71W
77Y
7O~
AAAAV
AAGIX
AAHPQ
AAIQE
AAMOA
AAQKA
AARTV
AASCR
AAWTL
AAXQO
AAYEP
ABASU
ABBUW
ABCQX
ABDIG
ABFRF
ABOCM
ABVCZ
ABXVJ
ABZAD
ABZZY
ACDDN
ACEWG
ACGFO
ACGFS
ACILI
ACLDA
ACWDW
ACWRI
ACXJB
ACXNZ
ACZKN
ADGGA
ADHPY
ADNKB
ADPDF
ADSXY
AE6
AEFWE
AENEX
AFBFQ
AFDTB
AGOPY
AHOMT
AHQNM
AHVBC
AIJEX
AINUH
AJCLO
AJIOK
AJNWD
AJNYG
AJZMW
AKCTQ
AKULP
ALKUP
ALMA_UNASSIGNED_HOLDINGS
ALMTX
AMJPA
AMKUR
AMNEI
AOHHW
AOQMC
BQLVK
CS3
DIWNM
DU5
E.X
EBS
EEVPB
ERAAH
EX3
F2K
F2L
F2M
F2N
F5P
FCALG
FD6
FIJ
FL-
GNXGY
GQDEL
GROUPED_DOAJ
H0~
HLJTE
HYE
HZ~
H~9
IKREB
IKYAY
IN~
IPNFZ
JK3
JK8
K8S
KD2
KMI
KQ8
L-C
N9A
N~7
N~B
O9-
OAG
OAH
OB2
OHH
OK1
OL1
OLB
OLG
OLH
OLU
OLV
OLY
OLZ
OPUJH
OUVQU
OVD
OVDNE
OVEED
OVIDH
OVLEI
OWV
OWW
OWZ
OXXIT
P2P
RIG
RLZ
RPM
RXW
S4R
S4S
TAF
TEORI
TSPGW
UNMZH
V2I
VVN
W3M
WOQ
WOW
X3V
X3W
XYM
YFH
YOC
ZFV
ZY1
.3C
.55
.GJ
1CY
53G
AAYXX
ADFPA
ADGHP
AE3
AFFNX
AFUWQ
AHRYX
BS7
BYPQX
CITATION
EJD
FW0
JF9
JG8
N4W
N~M
OCUKA
ODA
ORVUJ
OWU
P-K
R58
T8P
X7M
XXN
ZGI
ZXP
8L-
ACIJW
AWKKM
CGR
CUY
CVF
ECM
EIF
NPM
7X8
ADKSD
5PM
ID FETCH-LOGICAL-c4503-54e5798504ba0a1a97de401c6160e21a01aedb0e5a0a2d921fee8154f49407ef3
ISSN 0025-7974
1536-5964
IngestDate Thu Aug 21 18:42:31 EDT 2025
Mon Sep 08 06:52:31 EDT 2025
Wed Feb 19 02:29:47 EST 2025
Tue Jul 01 03:29:58 EDT 2025
Thu Apr 24 23:00:09 EDT 2025
Tue Aug 12 03:58:34 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 38
Language English
License This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c4503-54e5798504ba0a1a97de401c6160e21a01aedb0e5a0a2d921fee8154f49407ef3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ORCID 0000-0003-1946-1387
0000-00020-35043-08253
OpenAccessLink http://dx.doi.org/10.1097/MD.0000000000022190
PMID 32957346
PQID 2444873844
PQPubID 23479
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_7505345
proquest_miscellaneous_2444873844
pubmed_primary_32957346
crossref_primary_10_1097_MD_0000000000022190
crossref_citationtrail_10_1097_MD_0000000000022190
wolterskluwer_health_00005792-202009180-00043
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 20200918
PublicationDateYYYYMMDD 2020-09-18
PublicationDate_xml – month: 09
  year: 2020
  text: 20200918
  day: 18
PublicationDecade 2020
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: Hagerstown, MD
PublicationTitle Medicine (Baltimore)
PublicationTitleAlternate Medicine (Baltimore)
PublicationYear 2020
Publisher Lippincott Williams & Wilkins
Publisher_xml – name: Lippincott Williams & Wilkins
References Borgatti (R10-20230103) 2005; 27
van Eck Nees (R9-20230103) 2010; 84
Gan (R13-20230103) 2019; 98
Yeung (R22-20230103) 2018; 33
Dehdarirad (R12-20230103) 2019; 366
Kim (R25-20230103) 2019; 45
Gu (R20-20230103) 2020; 22
Liu (R11-20230103) 2020; 00
Gasparyan (R1-20230103) 2017; 32
Yang (R15-20230103) 2020; 192
Hernandez-Vasquez (R14-20230103) 2018; 11
Tijssen (R2-20230103) 1994; 18
Gonzalez (R19-20230103) 2018; 13
Wang (R18-20230103) 2018; 15
Romero (R21-20230103) 2019; 10
Jayaratne (R17-20230103) 2015; 10
Fardi (R23-20230103) 2017; 32
Mazaheri (R16-20230103) 2019; 10
References_xml – volume: 33
  start-page: 1240
  year: 2018
  ident: R22-20230103
  article-title: Citation network analysis of dental implant literature from 2007 to 2016
  publication-title: Int J Oral Maxillofac Implants
  doi: 10.11607/jomi.6727
– volume: 98
  start-page: e16782
  year: 2019
  ident: R13-20230103
  article-title: Mapping the knowledge structure and trends of epilepsy genetics over the past decade: A co-word analysis based on medical subject headings terms
  publication-title: Medicine (Baltimore)
  doi: 10.1097/MD.0000000000016782
– volume: 10
  start-page: 564
  year: 2019
  ident: R21-20230103
  article-title: Trends in sigma-1 receptor research: a 25-year bibliometric analysis
  publication-title: Front Pharmacol
  doi: 10.3389/fphar.2019.00564
– volume: 84
  start-page: 523
  year: 2010
  ident: R9-20230103
  article-title: Software survey: VOSviewer, a computer program for bibliometric mapping
  publication-title: Scientometrics
  doi: 10.1007/s11192-009-0146-3
– volume: 10
  start-page: 201
  year: 2019
  ident: R16-20230103
  article-title: Comparison of Intellectual Structure of Knowledge in International Journal of Preventive Medicine with MeSH: A Co-Word Analysis
  publication-title: Int J Prev Med
  doi: 10.4103/ijpvm.IJPVM_346_18
– volume: 13
  start-page: e0201435
  year: 2018
  ident: R19-20230103
  article-title: An author keyword analysis for mapping sport sciences
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0201435
– volume: 27
  start-page: 55
  year: 2005
  ident: R10-20230103
  article-title: Centrality and network flow
  publication-title: Soc Netw
  doi: 10.1016/j.socnet.2004.11.008
– volume: 192
  start-page: 105740
  year: 2020
  ident: R15-20230103
  article-title: Research trends of stem cells in ischemic stroke from 1999 to 2018: A bibliometric analysis
  publication-title: Clin Neurol Neurosurg
  doi: 10.1016/j.clineuro.2020.105740
– volume: 15
  start-page: 2181
  year: 2018
  ident: R18-20230103
  article-title: Exploring the emerging evolution trends of urban resilience research by scientometric analysis
  publication-title: Int J Environ Res Public Health
  doi: 10.3390/ijerph15102181
– volume: 00
  start-page: 1
  year: 2020
  ident: R11-20230103
  article-title: Worldwide tendency and perspectives in traumatic dental injuries: A bibliometric analysis over two decades (1999-2018)
  publication-title: Dent Traumatol
– volume: 45
  start-page: 186
  year: 2019
  ident: R25-20230103
  article-title: Classification of the journal category “oral surgery” in the Scopus and the science citation index expanded: flaws and suggestions
  publication-title: J Korean Assoc Oral Maxillofac Surg
  doi: 10.5125/jkaoms.2019.45.4.186
– volume: 32
  start-page: 173
  year: 2017
  ident: R1-20230103
  article-title: The journal impact factor: moving toward an alternative and combined scientometric approach
  publication-title: J Korean Med Sci
  doi: 10.3346/jkms.2017.32.2.173
– volume: 11
  year: 2018
  ident: R14-20230103
  article-title: A bibliometric analysis of the global research on biosimilars
  publication-title: J Pharm Policy Pract
  doi: 10.1186/s40545-018-0133-2
– volume: 366
  year: 2019
  ident: R12-20230103
  article-title: Bibliometric mapping of microbiology research topics (2012-16): a comparison by socioeconomic development and infectious disease vulnerability values
  publication-title: FEMS Microbiol Lett
  doi: 10.1093/femsle/fnz004
– volume: 10
  start-page: e0119503
  year: 2015
  ident: R17-20230103
  article-title: The evolution of dental journals from 2003 to 2012: a bibliometric analysis
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0119503
– volume: 22
  start-page: e15142
  year: 2020
  ident: R20-20230103
  article-title: Tracking knowledge evolution in cloud health care research: knowledge map and common word analysis
  publication-title: J Med Internet Res
  doi: 10.2196/15142
– volume: 18
  start-page: 98
  year: 1994
  ident: R2-20230103
  article-title: Mapping changes in science and technology: bibliometric co-occurrence analysis of the R&D literature
  publication-title: Eval Rev
  doi: 10.1177/0193841X9401800110
– volume: 32
  start-page: 555
  year: 2017
  ident: R23-20230103
  article-title: Top-cited articles in implant dentistry
  publication-title: Int J Oral Maxillofac Implants
  doi: 10.11607/jomi.5331
SSID ssj0013724
Score 2.3262734
Snippet Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings....
Supplemental Digital Content is available in the text Researchers seek to identify optimal journals for submission based on their studies but tend to rely on...
SourceID pubmedcentral
proquest
pubmed
crossref
wolterskluwer
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage e22190
SubjectTerms Bibliometrics
Dentistry
Medical Subject Headings
Observational Study
Periodicals as Topic
Republic of Korea
Title Analysis of research trends in Korean dentistry journals by assigning MeSH to author keywords
URI https://ovidsp.ovid.com/ovidweb.cgi?T=JS&NEWS=n&CSC=Y&PAGE=fulltext&D=ovft&AN=00005792-202009180-00043
https://www.ncbi.nlm.nih.gov/pubmed/32957346
https://www.proquest.com/docview/2444873844
https://pubmed.ncbi.nlm.nih.gov/PMC7505345
Volume 99
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1db9MwFLVgk6ZJCPE5ysdkJN4gw3HsOnmEtagaCiBtQ3tBkRM7NKIkU5tqgl_PdRyn6VohWB-iykmTNOf45vr6-lyEXinNRJ6GmadClXmMKepJTUw1dxJkPKVSNwG3-NNwcs5OLvjFKiGzWV1Sp0fZ763rSm6CKrQBrmaV7H8g250UGuA74AtbQBi2_4RxX1GkVe2ZmtTxNsv1YzU3cfZmKa6p6eZkIhbG5wSnufjeBEVifToxLqhc1tNq_hp69RWMSBd9tzVuZ-CNP_pezurCpud2QYQT3Wb2nlal3Gg8KcCI98MLMJY05RHCVXhhi0xEE14oZiaHp29aTV3cyJbcOdLOmg49HlmZcmdubT2kllZW2WXDjFt54Hhk1SXth4JtJf2jAYvLnw2yAY24CNg1Se3mJf0lPgafiAeM30a7VAgzlb_7-et4PFrNNQnKusK-8AecNlUk3m65g3205y637spsjE8202zvXFUmBWLxo1kB0fNjzu6hu-0ABL-zbLqPbunyAdpzAD9E3xypcJVjRypsSYWLEltS4Y5U2JEKp79wRypsSIXrCltSYUeqR-j8w_jseOK1NTi8jHFi8mY0F1HICUslkb6MBPRu4mdDf0g09SXxpVYp0Rz2UhVRP9c6BLc8Z9Dbhc6Dx2inrEr9BGGSqVyLLCU8FUylUcQDsB-BUn4uIxXoAaLucSZZK1Bv6qTMEpcoEY-S63AM0JvuR5dWn-Xvh790OCVgR83kmCx1tVwk4ObC2D0IGRugA4tbd0IH-ACJNUS7A4xG-_qespg2Wu0t-QbIW8M-saucm_uD50s90_XAdQ-tzEPw9MZXeob2V934Odqp50v9AvzmOj1s4k2HLf3_AKBZwTo
linkProvider Ovid
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lj9MwELagKwESQrwJTyOhnAg4fsTJoYeq7VJ2NwWpXVgOKHJih1agZLVJWfHvGedRKCuQyCWR7OTgGTufPd98g9ALbbjM0zDzdKgzj3NNPWWIreZOWCZSqkxz4BbPg9kxPzgRJx3bwubC2Oyz6vSVvTXrtH2w9XDsxnA5PFi48-nHxbBwx4vx8JP7fvRm2pxTW5aEOxmW3_PaHc0b_pWQEQUfsKf_fthmT7PLaC8QAAEGaO_dh-l08iveICnfFncFiN3rE0XydTxpNQ7bi8IMJ7v_sAvA9CK_8vp5aWPf1deG-v7bD2z_JrrRIU88al3lFrpkitvoStzF1u-gz70-CS5z3GkArXDdcGbxusCHJeDLAjeJvbZCHO7csMLpDwwQfP3FHrHg2CxmuC6x2tSr8gzDGnEO-9vqLjreny7HM68rvuBlXBBLmDAwgqEgPFVE-SqSYFbiZ4EfEEN9RXxldEqMgFaqI-rnxoSAx3IOZpYmZ_fQoCgL8wBhkuncyCwlIpVcp1EkGDgO09rPVaSZcRDthzPJOmVyWyDjW9JHyONJ8qcNHPRy-9JpK8zx7-7PezslMIFsVEQVptxUCeAb2LSxkHMH3W_ttv0go5GQjAcOkjsW3Xaw4ty7LcV61Yh0AxITjAsHeTu2T9r01uRvHvrwP_s_Q1dny_goOXo7P3yErtlWy2bxw8doUJ9tzBOATHX6tPP3n7dIC9E
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1La9wwEBZhA6FQSt91nyoUn-oi67G2Dz6EtbfbpN4ENmnTQzCyJXeXFjvE3ob8-4782HabUqgvNkg2RjOSvtHMfIPQG6W5V2R-7ihf5Q7nijpSE1PNnbBcZFTq9sAtmY9np_zgTJztoMFjapLP6ot35tYu0-bBlMMxduFJeLCwJ4tJ-MWex58X4dw-3n8ft8fUJkjCPo6m4bUdhdWPorGjo3DgZ0yijqSwuyhMUTDxd30ftt4R2j36FMfRL7-DR_mmyCtA7YGn6O-f2d7LbgDUm3GWt68q4wOvv7Uh8L9tZNO76E6PQPF-pzL30I4u76O9pPexP0DnA08JrgrccwEtcdPGzuJViQ8rwJklbhN8TaU43KtjjbNrDFB89dUcteBEL2a4qbBcN8vqEsNacQV2bv0QnU7jk8nM6YswODkXxAROaOEFviA8k0S6MvBAvMTNx-6YaOpK4kqtMqIFtFIVULfQ2gdcVnAQt6cL9giNyqrUTxAmuSq0l2dEZB5XWRAIBgrElHILGSimLUSH4UzznqHcFMr4ng6e8iRK_5SBhd5uXrroCDr-3f31IKcUJpLxjshSV-s6BZwDxhvzObfQ405umw8yGgiP8bGFvC2JbjoYku7tlnK1bMm6AZEJxoWFnC3Zp12aa_t_ML4UVivjp3L9Ls-fPf3P_q_QHuh_-vHD_PAZumUaTVCL6z9Ho-ZyrV8Acmqyl726_wTAYA1c
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Analysis+of+research+trends+in+Korean+dentistry+journals+by+assigning+MeSH+to+author+keywords&rft.jtitle=Medicine+%28Baltimore%29&rft.au=Jeong%2C+Sona&rft.au=Jeong%2C+Ji+Na&rft.date=2020-09-18&rft.pub=Lippincott+Williams+%26+Wilkins&rft.issn=0025-7974&rft.eissn=1536-5964&rft.volume=99&rft.issue=38&rft_id=info:doi/10.1097%2FMD.0000000000022190&rft_id=info%3Apmid%2F32957346&rft.externalDocID=PMC7505345
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0025-7974&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0025-7974&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0025-7974&client=summon