The new program is validated in a set of clinical pedigrees demonstrating its practical accuracy and relevance to the field. Collectively, the data are compelling and support the major conclusions of ...

Graph AI raises $3M Seed from Bessemer to scale Graph Safety, an AI-native pharmacovigilance platform that automates ADE ...

The atypical serine/threonine protein kinase mammalian target of rapamycin (mTOR) has an important role in the modulation of both innate and adaptive immune responses. A complex formed between the ...

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...

John Kindervag explains the value of security graphs for developing a containment strategy that stops both ransomware and ...

The dark blue circles on the left side of the graph show the direct measurements of calorie burn during training and racing.

The era has arrived in which artificial intelligence (AI) autonomously imagines and predicts the structures and properties of ...

Abstract: Graph convolutional neural networks (GCNs) have demonstrated effectiveness in processing graph structure. Due to the diversity and complexity of real-world graph data, heterogeneous GCN have ...

Abstract: The interactions between structured entities play important roles in a wide range of applications such as chemistry, material science, biology, and medical science. Recently, graph-based ...

TMTPOST -- Artificial intelligence will only achieve true general intelligence when it can autonomously discover new ...