Predicting the risk of ischemic stroke in patients with atrial fibrillation using heterogeneous drug–protein–disease network-based deep learning
Current risk assessment models for predicting ischemic stroke (IS) in patients with atrial fibrillation (AF) often fail to account for the effects of medications and the complex interactions between drugs, proteins, and diseases. We developed an interpretable deep learning model, the AF-Biological-I...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-06-01
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| Series: | APL Bioengineering |
| Online Access: | http://dx.doi.org/10.1063/5.0242570 |
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