2.2 Data analysis Our bibliometric analysis followed a general-to-detailed path, including an overview of countries/regions, institutions/authors, journal distribution, documents/references, keywords ...

The RLG module leverages the graph representation method (GRM) to extract features and assigns risk labels using unsupervised learning. The RA module employs spatiotemporal graph convolutional ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can ...

Graph-theoretical (GT) representations, conceptually analogous to chemical formulas, offer a powerful and versatile framework for describing the structure of nanomaterials─including complex assemblies ...

International Medical Graduates Representation at International Oncology Conference Meetings: An Analysis of ASCO Annual Meetings The following represents disclosure information provided by authors of ...

Graph representation learning has the property of causal inference of relation, and integrates graph structure with recommendation system, which effectively reduces the number of iterations required ...