Article

Automated generation of personalized trajectories of aging phenotypes with DyViA-GAN

2025-08-28

Abstract excerpt

With a general increase in human lifespan, the need for technological advances to develop strategies for healthy aging has assumed great importance. In the present study, our goal is to predict the progression of selected aging phenotypes in a given healthy individual as one continues aging past 65 years. Therefore, we developed a novel framework called Dynamic Views of Aging with conditional Generative Adversaria...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 743c5578-2197-5da5-8cdd-ff51c7362d6a
DOI: 10.1101/2025.08.22.671831

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Automated generation of personalized trajectories of aging phenotypes with DyViA-GANDOI 10.1101/2025.08.22.671831Read

Integrating Polygenic Risk Improves Generative Forecasting of Disease Trajectories.Semantic proximity Read

Creating a General-Purpose Generative Model for Healthcare Data based on Multiple Clinical StudiesSemantic proximity Read

HyTrax: Deep Sequential Modeling of Serial Musculoskeletal Measurements for Fracture Prediction in the Women's Health Initiative with External Evaluation in the Framingham Heart StudySemantic proximity Read

Learning the natural history of human disease with generative transformersSemantic proximity Read

Using deep learning to analyze the compositeness of musculoskeletal aging reveals that spine, hip and knee age at different rates, and are associated with different genetic and non-genetic factorsSemantic proximity Read

Conditional deep generative modeling of blood-based infrared spectra enables controlled in-silico phenotyping studiesSemantic proximity Read

Novel biological age model using explainable automated CT-based cardiometabolic biomarkers for phenotypic prediction of longevitySemantic proximity Read

A Utility-Based Machine Learning-Driven Personalized Lifestyle Recommendation for Cardiovascular Disease PreventionSemantic proximity Read

Generative Adversarial Networks for Modeling Clinical Biomarker Profiles in Under-Represented GroupsSemantic proximity Read

Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders.Semantic proximity Read

Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?Semantic proximity Read

High-Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million-Patient Diabetes CohortSemantic proximity Read