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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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PURPOSE: Text-mining has been shown to be useful for understanding the clinical characteristics and patients' concerns regarding a specific disease. Low back pain (LBP) is the most common disease in modern society and has a wide variety of causes and symptoms. On the other hand, it is difficult to understand the clinical characteristics and the needs as well as demands of patients with LBP because of the various clinical characteristics. This study examined online texts on LBP to determine of text-mining can help better understand general characteristics of LBP and its specific elements. METHODS: Online data from www.spine-health.com were used for text-mining. Keyword frequency analysis was performed first on the complete text of postings (full-text analysis). Only the sentences containing the highest frequency word, pain, were selected. Next, texts including the sentences were used to re-analyze the keyword frequency (pain-text analysis). RESULTS: Keyword frequency analysis showed that pain is of utmost concern. Full-text analysis was dominated by structural, pathological, and therapeutic words, whereas pain-text analysis was related mainly to the location and quality of the pain. CONCLUSION: The present study indicated that text-mining for a specific element (keyword) of a particular disease could enhance the understanding of the specific aspect of the disease. This suggests that a consideration of the text source is required when interpreting the results. Clinically, the present results suggest that clinicians pay more attention to the pain a patient is experiencing, and provide information based on medical knowledge.
목차
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참고문헌 (21)
참고문헌 신청
Mazzoni D / 2014 / Sharing experiences and social support requests in an Internet forum for patients with systemic lupus erythematosus / J Health Psychol 19(5):689~696
Allen C / 2016 / Long-term condition self-management support in online communities : a meta-synthesis of qualitative papers / J Med Internet Res 18(3):e61
Kingod N / 2017 / Online peer-to-peer communities in the daily lives of people with chronic illness: a qualitative systematic review / Qual Health Res 27(1):89~99
Feldman R / 2007 / The text mining handbook: advanced approaches in analyzing unstructured data / Cambridge University Press
Bellika J / 2014 / Text mining of web-based medical content (Vol. 1) / Walter de Gruyter GmbH & Co KG
Allen C / 2016 / Long-term condition self-management support in online communities : a meta-synthesis of qualitative papers / J Med Internet Res 18(3):e61
Kingod N / 2017 / Online peer-to-peer communities in the daily lives of people with chronic illness: a qualitative systematic review / Qual Health Res 27(1):89~99
Feldman R / 2007 / The text mining handbook: advanced approaches in analyzing unstructured data / Cambridge University Press
Bellika J / 2014 / Text mining of web-based medical content (Vol. 1) / Walter de Gruyter GmbH & Co KG
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