Abstract: In a large hospital system, a network of hospitals relies on electronic health records (EHRs) to make informed decisions regarding their patients in various clinical domains. Consequently, ...
Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...
This article was co-authored with Emma Myer, a student at Washington and Lee University who studies Cognitive/Behavioral Science and Strategic Communication. In today’s digital age, social media has ...
Abstract: Deep-learning is widely used in modulation classification to reduce labor and improve the efficiency. Graph convolutional network (GCN) is a type of feature extraction network for graph data ...
Clique enumeration seeks to list all complete subgraphs within a larger network, a task central to understanding cohesive structures in domains as diverse as social science, bioinformatics and ...
The graph theory is an old subject and nowadays it has become a method widely used in various fields of mathematics, computer science, engineering, chemistry, among others. Its application ranges from ...
Speaking at WSJ Opinion Live in Washington, D.C., WSJ Editorial Page Editor Paul Gigot and SandboxAQ CEO Jack Hidary discuss Large Quantitative Models (LQMs) and their role in AI applications, the ...
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