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Found 3 papers, 1 papers with code
Predicting the Risk of Ischemic Stroke in Patients with Atrial Fibrillation using Heterogeneous Drug-protein-disease Network-based Deep Learning
The model integrates drug-protein-disease pathways and real-world clinical data of AF patients to generate the IS risk and potential pathways for each patient.
On the Compressibility of Quantized Large Language Models
Deploying Large Language Models (LLMs) on edge or mobile devices offers significant benefits, such as enhanced data privacy and real-time processing capabilities.
Accurate Fine-grained Layout Analysis for the Historical Tibetan Document Based on the Instance Segmentation
The experimental results show that the proposed method delivers a decent 72. 7% average precision on our dataset.
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