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View article: A multilayer network analysis of cardiovascular–depression comorbidity reveals symptom-specific molecular biomarkers
A multilayer network analysis of cardiovascular–depression comorbidity reveals symptom-specific molecular biomarkers Open
Background Cardiovascular diseases (CVD) and depression frequently co-occur, yet the biological mechanisms underpinning this comorbidity remain poorly understood. This may reflect complex, non-linear associations across multiple biological…
View article: Efficient Search Algorithms for Identifying Synergistic Associations in High-Dimensional Datasets
Efficient Search Algorithms for Identifying Synergistic Associations in High-Dimensional Datasets Open
In recent years, there has been a notably increased interest in the study of multivariate interactions and emergent higher-order dependencies. This is particularly evident in the context of identifying synergistic sets, which are defined a…
View article: Bias in O-Information Estimation
Bias in O-Information Estimation Open
Higher-order relationships are a central concept in the science of complex systems. A popular method of attempting to estimate the higher-order relationships of synergy and redundancy from data is through the O-information. It is an inform…
View article: Multilayer Network of Cardiovascular Diseases and Depression via Multipartite Projection
Multilayer Network of Cardiovascular Diseases and Depression via Multipartite Projection Open
Cardiovascular diseases (CVD) and depression exhibit significant comorbidity, which is highly predictive of poor clinical outcomes. Yet, the underlying biological pathways remain challenging to decipher, presumably due to the non-linear as…
View article: Predicting early-stage coronary artery disease using machine learning and routine clinical biomarkers improved by augmented virtual data
Predicting early-stage coronary artery disease using machine learning and routine clinical biomarkers improved by augmented virtual data Open
Aims Coronary artery disease (CAD) is a highly prevalent disease with modifiable risk factors. In patients with suspected obstructive CAD, evaluating the pre-test probability model is crucial for diagnosis, although its accuracy remains co…
View article: Understanding multimorbidity requires sign-disease networks and higher-order interactions, a perspective
Understanding multimorbidity requires sign-disease networks and higher-order interactions, a perspective Open
Background: Count scores, disease clustering, and pairwise associations between diseases remain ubiquitous in multimorbidity research despite two major shortcomings: they yield no insight into plausible mechanisms underlying multimorbidity…