DAFTED: Decoupled Asymmetric Fusion of Tabular and Echocardiographic Data for Cardiac Hypertension Diagnosis
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908547813474304 |
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| author | Stym-Popper, Jérémie Painchaud, Nathan Rambour, Clément Courand, Pierre-Yves Thome, Nicolas Bernard, Olivier |
| author_facet | Stym-Popper, Jérémie Painchaud, Nathan Rambour, Clément Courand, Pierre-Yves Thome, Nicolas Bernard, Olivier |
| contents | Multimodal data fusion is a key approach for enhancing diagnosis in medical applications. We propose an asymmetric fusion strategy starting from a primary modality and integrating secondary modalities by disentangling shared and modality-specific information. Validated on a dataset of 239 patients with echocardiographic time series and tabular records, our model outperforms existing methods, achieving an AUC over 90%. This improvement marks a crucial benchmark for clinical use. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_15990 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DAFTED: Decoupled Asymmetric Fusion of Tabular and Echocardiographic Data for Cardiac Hypertension Diagnosis Stym-Popper, Jérémie Painchaud, Nathan Rambour, Clément Courand, Pierre-Yves Thome, Nicolas Bernard, Olivier Computer Vision and Pattern Recognition Multimodal data fusion is a key approach for enhancing diagnosis in medical applications. We propose an asymmetric fusion strategy starting from a primary modality and integrating secondary modalities by disentangling shared and modality-specific information. Validated on a dataset of 239 patients with echocardiographic time series and tabular records, our model outperforms existing methods, achieving an AUC over 90%. This improvement marks a crucial benchmark for clinical use. |
| title | DAFTED: Decoupled Asymmetric Fusion of Tabular and Echocardiographic Data for Cardiac Hypertension Diagnosis |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.15990 |