Discovery of potential comorbidity relationship based on co-occurrence and citation of entities

Corresponding author: Tang Xiaoli, tang.xiaoli@imicams.ac.cn

DOI: 10.12201/bmr.202203.00003

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  Abstract: PurposeWith the aggravation of population aging, comorbidity has become an increasingly serious health problem. Accurate prediction of comorbidity combination can provide effective literature evidence-based support for the formulation of treatment plans and measures and the prevention, treatment and management of comorbidity.MethodSPO semantic mining and entity recognition technology were used to mine the comorbidity relationship in the literature. On this basis, the comorbidity network was constructed, and the link prediction method was used to predict the potential comorbidity combination.ConclusionEmpirical results in the field of diabetes can prove the effectiveness and accuracy of the model. Compared with the unimproved method, the prediction effect is better, and it can provide reference for the pathogenesis, disease prevention, clinical diagnosis and treatment of comorbidity.

  Key words: comorbidity; link prediction; SPO semantic mining; citing sentences

  Submit time: 18 March 2022

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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