and colleagues introduced a multimodal computational framework for patients' stratification and prognosis prediction (VAE-Surv). VAE-Surv integrates a variational autoencoder (VAE), which reduces ...

This is called multimodal AI. For example, combining medical imaging with genomic data has been shown to improve the accuracy of cancer diagnosis and treatment planning. Integrating these ...

However, Multimodal AI has emerged to address the increasing complexity of real-world problems, enabling industries to gain new insights by integrating and processing various data types.

This article explains how to use a PyTorch neural autoencoder to find anomalies in a dataset. A good way to see where this article is headed is to take a look at the screenshot of a demo program in ...

This is called dimensionality reduction. The two most common techniques for dimensionality reduction are using PCA (principal component analysis) and using a neural autoencoder. This article explains ...