A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank
Background Multimorbidities greatly increase the global health burdens, but the landscapes
of their genetic risks have not been systematically investigated. Methods We used the …
of their genetic risks have not been systematically investigated. Methods We used the …
Interleukin-17 links inflammatory cross-talks between comorbid psoriasis and atherosclerosis
Y Wang, J Zang, C Liu, Z Yan, D Shi - Frontiers in Immunology, 2022 - frontiersin.org
Psoriasis is a chronic, systemic, immune-mediated inflammatory disorder that is associated
with a significantly increased risk of cardiovascular disease (CVD). Studies have shown that …
with a significantly increased risk of cardiovascular disease (CVD). Studies have shown that …
Machine learning models for prediction of co-occurrence of diabetes and cardiovascular diseases: a retrospective cohort study
Background Diabetic mellitus (DM) and cardiovascular diseases (CVD) cause significant
healthcare burden globally and often co-exists. Current approaches often fail to identify …
healthcare burden globally and often co-exists. Current approaches often fail to identify …
Analysis of disease comorbidity patterns in a large-scale China population
M Guo, Y Yu, T Wen, X Zhang, B Liu, J Zhang… - BMC medical …, 2019 - Springer
Background Disease comorbidity is popular and has significant indications for disease
progress and management. We aim to detect the general disease comorbidity patterns in …
progress and management. We aim to detect the general disease comorbidity patterns in …
NSL2CD: identifying potential circRNA–disease associations based on network embedding and subspace learning
Q Xiao, Y Fu, Y Yang, J Dai, J Luo - Briefings in Bioinformatics, 2021 - academic.oup.com
Many studies have evidenced that circular RNAs (circRNAs) are important regulators in
various pathological processes and play vital roles in many human diseases, which could …
various pathological processes and play vital roles in many human diseases, which could …
Learning from low-rank multimodal representations for predicting disease-drug associations
Background Disease-drug associations provide essential information for drug discovery and
disease treatment. Many disease-drug associations remain unobserved or unknown, and …
disease treatment. Many disease-drug associations remain unobserved or unknown, and …
Relation prediction of co-morbid diseases using knowledge graph completion
Co-morbid disease condition refers to the simultaneous presence of one or more diseases
along with the primary disease. A patient suffering from co-morbid diseases possess more …
along with the primary disease. A patient suffering from co-morbid diseases possess more …
MorbidGCN: prediction of multimorbidity with a graph convolutional network based on integration of population phenotypes and disease network
Exploring multimorbidity relationships among diseases is of great importance for
understanding their shared mechanisms, precise diagnosis and treatment. However, the …
understanding their shared mechanisms, precise diagnosis and treatment. However, the …
Constructing disease similarity networks based on disease module theory
Quantifying the associations between diseases is now playing an important role in modern
biology and medicine. Actually discovering associations between diseases could help us …
biology and medicine. Actually discovering associations between diseases could help us …
A novel approach for disease comorbidity prediction using weighted association rule mining
KS Lakshmi, G Vadivu - Journal of Ambient Intelligence and Humanized …, 2019 - Springer
Disease comorbidity prediction has gained the attention of many researchers during the past
years. Bulk creation of clinical data in the form of electronic health records (EHRs) and …
years. Bulk creation of clinical data in the form of electronic health records (EHRs) and …