Results 101 to 110 of about 36,296 (256)
Straight-through and autoregressive influence estimation for influence maximization
Influence maximization(IM) aims to select a set of seed nodes in a social network to maximize the expected spread of information. It has long been a prominent research topic in statistical physics of social network analysis; however, traditional methods ...
Juyuan Zhang +5 more
doaj +1 more source
A new stochastic diffusion model for influence maximization in social networks. [PDF]
Rezvanian A, Vahidipour SM, Meybodi MR.
europepmc +1 more source
ABSTRACT Background Ischemic stroke, a major cause of mortality and long‐term disability, results from the abrupt cessation of cerebral blood flow due to vascular occlusion or rupture. Icosapent Ethyl (EPA‐EE), approved for hypertriglyceridemia, has anti‐inflammatory and antithrombotic properties that may lessen ischemic damage.
Mitra Mahmoudi Meymand +5 more
wiley +1 more source
Advancing Stroke Clinical Trials Using Community Engagement and Implementation Science Approaches
ABSTRACT Stroke clinical trials are essential for advancing stroke care but can face challenges with recruitment, retention, clinical relevance, and translation into real‐world practice. We propose that integrating community engagement and implementation science approaches into stroke trials can help address these needs.
Lesli E. Skolarus +2 more
wiley +1 more source
Identifying vital nodes for influence maximization in attributed networks. [PDF]
Wang Y, Zheng Y, Liu Y.
europepmc +1 more source
ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu +7 more
wiley +1 more source
The influence maximization problem that has drawn a great deal of attention from researchers aims to identify a subset of influential spreaders that can maximize the expected influence spread in social networks.
Jianxin Tang +4 more
doaj +1 more source
HEDV-Greedy: An Advanced Algorithm for Influence Maximization in Hypergraphs
Influence maximization (IM) has shown wide applicability in various fields over the past few decades, e.g., viral marketing, rumor control, and prevention of infectious diseases.
Haosen Wang, Qingtao Pan, Jun Tang
doaj +1 more source
Objective Clinical response to mycophenolic acid (MPA) is highly heterogeneous; thus, therapeutic drug level monitoring (TDM) may help improve treatment efficacy. This systematic review and meta‐analysis examined therapeutic ranges for MPA levels associated with better outcomes and safety in patients with systemic lupus erythematosus (SLE ...
Zahraa Qamhieh +5 more
wiley +1 more source
Competitive influence maximization in biased community networks: An adaptive algorithmic approach
Influence maximization is a widely recognized problem that aims to identify a limited set of influencers to maximize the coverage of influence propagation in a social network.
YuLe Zou
doaj +1 more source

