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AI in HealthcarearXiv cs.LGPublished: Apr 9, 2026, 13:00 JST

Researchers optimize variational autoencoders to better predict survival risk in multiple myeloma by balancing latent space regularization with prognostic accuracy.

Researchers optimize variational autoencoders to better predict survival risk in multiple myeloma by balancing latent space regularization with prognostic accuracy.

MO-RiskVAE extends the MyeVAE framework to integrate multiple data types (omics and clinical) for improved survival prediction in multiple myeloma patients

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