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Results for "graph learning"

PDNS-Net: A Large Heterogeneous Graph Benchmark Dataset of Network Resolutions for Graph Learning

arXiv · Mar 15

The Qatar Computing Research Institute (QCRI) has introduced PDNS-Net, a large heterogeneous graph dataset for malicious domain classification, containing 447K nodes and 897K edges. It is significantly larger than existing heterogeneous graph datasets like IMDB and DBLP. Preliminary evaluations using graph neural networks indicate that further research is needed to improve model performance on large heterogeneous graphs. Why it matters: This dataset will enable researchers to develop and benchmark graph learning algorithms on a scale relevant to real-world cybersecurity applications, particularly for identifying and mitigating malicious online activity.

Improving diagnosis of neurodegenerative diseases

MBZUAI · Invalid Date

MBZUAI valedictorian Salma Hassan developed a multimodal graph learning approach for early dementia diagnosis and prognosis. Her master's thesis focused on differential diagnosis to identify specific dementia subtypes and predicting cognitive decline in preclinical patients. The AI model leverages brain imaging, genetics, and clinical records to improve diagnostic accuracy. Why it matters: This research can improve early detection and resource allocation for dementia management, especially in developing countries.