Generative AI Models in Time-Varying Biomedical Data: Scoping Review.

ABSTRACT:

Background

Trajectory modeling is a long-standing challenge in the application of computational methods to health care. In the age of big data, traditional statistical and machine learning methods do not achieve satisfactory results as they often fail to capture the complex underlying distributions of multimodal health data and long-term dependencies throughout medical histories. Recent advances in generative artificial intelligence (AI) have provided powerful tools to represent complex distributions and patterns with minimal underlying assumptions, with major impact in fields such as finance and environmental sciences, prompting researchers to apply these methods for disease modeling in health care.

Objective

While AI methods have proven powerful, their application in clini

SUBMITTER: He R 

PROVIDER: S-EPMC11933772 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature