A novel self-attentive deep learning for predicting pregnancy outcome after hysteroscopic adhesiolysis in patients with intrauterine adhesions
This study presents SDL-IUAs, a novel deep learning framework that employs a self-attention mechanism to predict pregnancy outcomes in patients with intrauterine adhesions (IUAs) following hysteroscopic adhesiolysis. By integrating random forest-based feature importance analysis with self-attention,...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-04-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0248831 |
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