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What is VAE-Enhanced Survival Predictions for Pancreatic Cancer about?

This study explores the use of Variational Autoencoders (VAE) to enhance predictions of in-hospital survival for pancreatic cancer patients using machine learning techniques. By augmenting a limited dataset of biochemical blood test results, the research identifies Elastic Net, Decision Trees, and Radial Basis Function Support Vector Machine as the most effective models, achieving a reduction in Mean Absolute Error to approximately 10 days. The findings underscore the potential of VAE-assisted ensemble lear

Author

J.A.S SANTHOSH

Language

EN