Abstract
During the last 30 years, Alzheimer's disease (AD) research, aiming to understand the pathophysiology and to improve the diagnosis, management, and, ultimately, treatment of the disease, has grown rapidly. Recently, some studies have used simple bibliometric approaches to investigate research trends and advances in the field. In our study, we map the AD research field by applying entitymetrics, an extended concept of bibliometrics, to capture viewpoints of indexers, authors, or citers. Using the full-text documents with reference section retrieved from PubMed Central, we constructed four types of networks: MeSH-MeSH (MM), MeSH-Citation-MeSH (MCM), Keyphrase-Keyphrase (KK), and Keyphrase-Citation-Keyphrase (KCK) networks. The working hypothesis was that MeSH, keyphrase, and citation relationships reflect the views of indexers, authors, and/or citers, respectively. In comparative network and centrality analysis, we found that those views are different: indexers emphasize amyloid-related entities, including methodological terms, while authors focus on specific biomedical terms, including clinical syndromes. The more dense and complex networks of citing relationships reported in our study, to a certain extent reflect the impact of basic science discoveries in AD. However, none of these could have had clinical relevance for patients without close collaboration between investigators in translational and clinical-related AD research (reflected in indexers and authors' networks). Our approach has relevance for researches in the field, since they can identify relations between different developments which are not otherwise evident. These developments combined with advanced visualization techniques, might aid the discovery of novel interactions between genes and pathways or used as a resource to advance clinical drug development.
| Original language | English |
|---|---|
| Pages (from-to) | 1207-1222 |
| Number of pages | 16 |
| Journal | Journal of Alzheimer's Disease |
| Volume | 45 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2015 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Neuroscience(all)
- Clinical Psychology
- Geriatrics and Gerontology
- Psychiatry and Mental health
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A bird's-eye view of Alzheizmer's disease research : Reflecting different perspectives of indexers, authors, or citers in mapping the field. / Lee, Dahee; Kim, Won Chul; Charidimou, Andreas; Song, Min.
In: Journal of Alzheimer's Disease, Vol. 45, No. 4, 01.01.2015, p. 1207-1222.Research output: Contribution to journal › Article
TY - JOUR
T1 - A bird's-eye view of Alzheizmer's disease research
T2 - Reflecting different perspectives of indexers, authors, or citers in mapping the field
AU - Lee, Dahee
AU - Kim, Won Chul
AU - Charidimou, Andreas
AU - Song, Min
PY - 2015/1/1
Y1 - 2015/1/1
N2 - During the last 30 years, Alzheimer's disease (AD) research, aiming to understand the pathophysiology and to improve the diagnosis, management, and, ultimately, treatment of the disease, has grown rapidly. Recently, some studies have used simple bibliometric approaches to investigate research trends and advances in the field. In our study, we map the AD research field by applying entitymetrics, an extended concept of bibliometrics, to capture viewpoints of indexers, authors, or citers. Using the full-text documents with reference section retrieved from PubMed Central, we constructed four types of networks: MeSH-MeSH (MM), MeSH-Citation-MeSH (MCM), Keyphrase-Keyphrase (KK), and Keyphrase-Citation-Keyphrase (KCK) networks. The working hypothesis was that MeSH, keyphrase, and citation relationships reflect the views of indexers, authors, and/or citers, respectively. In comparative network and centrality analysis, we found that those views are different: indexers emphasize amyloid-related entities, including methodological terms, while authors focus on specific biomedical terms, including clinical syndromes. The more dense and complex networks of citing relationships reported in our study, to a certain extent reflect the impact of basic science discoveries in AD. However, none of these could have had clinical relevance for patients without close collaboration between investigators in translational and clinical-related AD research (reflected in indexers and authors' networks). Our approach has relevance for researches in the field, since they can identify relations between different developments which are not otherwise evident. These developments combined with advanced visualization techniques, might aid the discovery of novel interactions between genes and pathways or used as a resource to advance clinical drug development.
AB - During the last 30 years, Alzheimer's disease (AD) research, aiming to understand the pathophysiology and to improve the diagnosis, management, and, ultimately, treatment of the disease, has grown rapidly. Recently, some studies have used simple bibliometric approaches to investigate research trends and advances in the field. In our study, we map the AD research field by applying entitymetrics, an extended concept of bibliometrics, to capture viewpoints of indexers, authors, or citers. Using the full-text documents with reference section retrieved from PubMed Central, we constructed four types of networks: MeSH-MeSH (MM), MeSH-Citation-MeSH (MCM), Keyphrase-Keyphrase (KK), and Keyphrase-Citation-Keyphrase (KCK) networks. The working hypothesis was that MeSH, keyphrase, and citation relationships reflect the views of indexers, authors, and/or citers, respectively. In comparative network and centrality analysis, we found that those views are different: indexers emphasize amyloid-related entities, including methodological terms, while authors focus on specific biomedical terms, including clinical syndromes. The more dense and complex networks of citing relationships reported in our study, to a certain extent reflect the impact of basic science discoveries in AD. However, none of these could have had clinical relevance for patients without close collaboration between investigators in translational and clinical-related AD research (reflected in indexers and authors' networks). Our approach has relevance for researches in the field, since they can identify relations between different developments which are not otherwise evident. These developments combined with advanced visualization techniques, might aid the discovery of novel interactions between genes and pathways or used as a resource to advance clinical drug development.
UR - http://www.scopus.com/inward/record.url?scp=84928107660&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84928107660&partnerID=8YFLogxK
U2 - 10.3233/JAD-142688
DO - 10.3233/JAD-142688
M3 - Article
VL - 45
SP - 1207
EP - 1222
JO - Journal of Alzheimer's Disease
JF - Journal of Alzheimer's Disease
SN - 1387-2877
IS - 4
ER -