Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study
This study evaluates the performance of deep learning models in the prediction of the end time of procedures performed in the cardiac catheterization laboratory (cath lab). We employed only the clinical phases derived from video analysis as input to the algorithms. Our results show that InceptionTim...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Computer Assisted Surgery |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/24699322.2025.2466426 |
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