Symptom clusters based on symptom scores (n = 249).

Symptom clusters based on symptom scores (n = 249).

<p>Symptom clusters based on symptom scores (n = 249).</p>

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Bibliographic Details
Main Author:	Hang Gao (1457464) (author)
Other Authors:	Xiaoxue Wen (3723001) (author), Xiaoli Sun (140478) (author), Yuwei Liu (589589) (author), Jianwen Hou (414198) (author), Danwen Zheng (11925068) (author), Hejia Chen (21696295) (author), Lingfang Ma (21696298) (author), Yufang Zhou (15262094) (author), Xinyan Yu (158875) (author)
Published:	2025
Subjects:	Medicine Biotechnology Cancer Infectious Diseases Biological Sciences not elsewhere classified selecting appropriate targets r programming language perceptual &# 8212 offering important insights network &# 8217 intricate network analysis exploratory factor analysis zhejiang cancer hospital symptom network analysis multidimensional symptom network multidimensional symptom experience entire symptom network discover symptom clusters constructed contemporaneous networks way lung cancer significant among survivors chinese version ). contemporaneous symptom networks 43 ), cough lung cancer survivors symptom management burden precise symptom management lung cancer immunotherapy network structure using 69 ), cough lung cancer symptom networks symptom management symptom burden 69 ). symptom patterns 72 ), precise interventions conducted using 73 ). xlink "> target actions synergistic relationships study seeks study demonstrates statistically analyze specific module significantly differ radically changes overall strength nodal intensity interventions focused healthcare professionals female groups effectively reduce
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