Japanese Lung Cancer Research Trends and Performance in Science Citation Index

Overview

Journal Intern Med

Specialty General Medicine

Date 2010 Oct 22

PMID 20962440

Citations 24

Authors

Yuh-Shan Ho

Hiroaki Satoh

Shih-Yuan Lin

Affiliations

Soon will be listed here.

Abstract

Objective: This study was undertaken to explore a bibliometric approach to quantitatively assess current research trends in lung cancer in Japan, using the related literature in the Science Citation Index (SCI) database from 1991 to 2008.

Materials And Methods: Articles were analyzed by the scientific output and research performances of individuals, institutes, and collaborative countries with Japan. Distribution of words in the article title, author keywords, and KeyWords Plus in different periods was applied to evaluate research trends by the frequency of keywords used.

Results: Keyword analysis indicated that there has been a strategy to connect molecular biology with clinical practice. Researchers in Japan have published high impact articles related to non-small cell and small cell lung cancer.

Conclusion: Finally, this study highlights the topics in lung cancer research that are becoming popular in Japan.

Citing Articles

Analyzing shifts in age-related macular degeneration research trends since 2014: A bibliometric study with triple-map Sankey diagrams (TMSD).

Lin H, Chou W, Chien T, Yeh Y, Kuo S, Hsu S Medicine (Baltimore). 2024; 103(3):e36547.

PMID: 38241545 PMC: 10798733. DOI: 10.1097/MD.0000000000036547.

Trends and hotspots related to traditional and modern approaches on acupuncture for stroke: A bibliometric and visualization analysis.

Chuang C, Chou W, Chien T, Jen T Medicine (Baltimore). 2023; 102(48):e35332.

PMID: 38050290 PMC: 10695603. DOI: 10.1097/MD.0000000000035332.

Exploring the top-cited literature in telerehabilitation for joint replacement using the descriptive, diagnostic, predictive, and prescriptive analytics model: A thematic and bibliometric analysis.

Chuang H, Ho S, Chou W, Tsai C Medicine (Baltimore). 2023; 102(48):e36475.

PMID: 38050200 PMC: 10695623. DOI: 10.1097/MD.0000000000036475.

A modern approach with follower-leading clustering algorithm for visualizing author collaborations and article themes in skin cancer research: A bibliometric analysis.

Lai P, Chou W, Chien T, Lai F Medicine (Baltimore). 2023; 102(44):e34801.

PMID: 37933006 PMC: 10627629. DOI: 10.1097/MD.0000000000034801.

Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review.

Ezugwu A, Oyelade O, Ikotun A, Agushaka J, Ho Y Arch Comput Methods Eng. 2023; :1-31.

PMID: 37359741 PMC: 10148585. DOI: 10.1007/s11831-023-09930-z.