The World Health Organization reports a steady increase in cancer patients worldwide, marking it as a major health threat. Preventing and treating cancer has become a global priority, with identifying ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

A team of researchers led by professor Xindong Wu in Hefei, China has developed an unsupervised entity alignment framework to improve the process of searching for related information in multiple ...

For predicting relapse in 1,387 patients with early-stage (I-II) NSCLC from the Spanish Lung Cancer Group data (average age 65.7 years, female 24.8%, male 75.2%), we train tabular and graph machine ...

Machine learning, with its ability to analyze large datasets and identify patterns, is particularly well-suited to address the challenges presented by the vast and complex data generated in ...

A knowledge graph, is a graph that depicts the relationship between real-world entities, such as objects, events, situations, and concepts. This information is typically stored in a graph database and ...