Weakly-Supervised Multimodal Learning on MIMIC-CXR
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Abstract (arXiv)
Multimodal data integration and label scarcity pose significant challenges for machine learning in medical settings. To address these issues, we conduct an in-depth evaluation of the newly proposed Multimodal Variational Mixture-of-Experts (MMVM) VAE on the challenging MIMIC-CXR dataset. Our analysis demonstrates that the MMVM VAE consistently outperforms other multimodal VAEs and fully supervised approaches, highlighting its strong potential for real-world medical applications.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Nov 2024.
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