The Research Trends and Keywords Modeling of Shoulder Rehabilitation using the Text-mining Technique (텍스트 마이닝 기법을 활용한 어깨 재활 연구분야 동향과 키워드 모델링)

Jun-hee Kim (김준희); Sung-hoon, Jung (정성훈); Hwang ui-jae (황의재)

The Research Trends and Keywords Modeling of Shoulder Rehabilitation using the Text-mining Technique

Journal of the Korean Society of Physical Medicine
Abbr : J Korean Soc Phys Med
2021, 16(2), pp.91-100
Publisher : The Korean Society of Physical Medicine
Research Area : Medicine and Pharmacy > Physical Therapy > Other physical therapy
Received : April 12, 2021
Accepted : May 2, 2021
Published : May 31, 2021

Jun-hee Kim ¹, Sung-hoon, Jung ², Hwang ui-jae ²

¹코리아테크
²연세대학교

Accredited

ABSTRACT

PURPOSE: This study analyzed the trends and characteristics of shoulder rehabilitation research through keyword analysis, and their relationships were modeled using text mining techniques. METHODS: Abstract data of 10,121 articles in which abstracts were registered on the MEDLINE of PubMed with 'shoulder' and 'rehabilitation' as keywords were collected using python. By analyzing the frequency of words, 10 keywords were selected in the order of the highest frequency. Word-embedding was performed using the word2vec technique to analyze the similarity of words. In addition, the groups were classified and analyzed based on the distance (cosine similarity) through the t-SNE technique. RESULTS: The number of studies related to shoulder rehabilitation is increasing year after year, keywords most frequently used in relation to shoulder rehabilitation studies are ‘patient’, ‘pain’, and ‘treatment’. The word2vec results showed that the words were highly correlated with 12 keywords from studies related to shoulder rehabilitation. Furthermore, through t-SNE, the keywords of the studies were divided into 5 groups. CONCLUSION: This study was the first study to model the keywords and their relationships that make up the abstracts of research in the MEDLINE of Pub Med related to ‘shoulder’ and ‘rehabilitation’ using text-mining techniques. The results of this study will help increase the diversifying research topics of shoulder rehabilitation studies to be conducted in the future.

KEYWORDS

Research trend, Shoulder rehabilitation, t-SNE, Text-mining, word2vec

Citation status

* References for papers published after 2023 are currently being built.

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