Article

Large Language Models forecast Patient Health Trajectories enabling Digital Twins

2024-07-07

Abstract excerpt

<h4>Background</h4> Generative artificial intelligence (AI) accelerates the development of digital twins, which enable virtual representations of real patients to explore, predict and simulate patient health trajectories, ultimately aiding treatment selection and clinical trial design. Recent advances in forecasting utilizing generative AI, in particular large language models (LLMs), highlights untapped potential...

Topics

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

Identifiers and source

Literature Corpus work: 97c99ab5-b736-5e90-94a4-e5429a850ab5
DOI: 10.1101/2024.07.05.24309957

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Large Language Models forecast Patient Health Trajectories enabling Digital TwinsDOI 10.1101/2024.07.05.24309957Read

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

Enformer: An encoder-decoder generative model to enhance prediction of disease outcomes using electronic health recordsSemantic proximity Read

Large Language Models for Cardiovascular Disease, Cancer, and Mental Disorders: A Review of Systematic ReviewsSemantic proximity Read

SurvivEHR: a competing risks, time-to-event foundation model for multiple long-term conditions from primary care electronic health recordsSemantic proximity Read

Generating Synthetic Mixed-type Longitudinal Electronic Health Records for Artificial Intelligent ApplicationsSemantic proximity Read

Revolutionizing Personalized Medicine with Generative AI: A Systematic ReviewSemantic proximity Read

Integrating Genomics into Multimodal EHR Foundation ModelsSemantic proximity Read

Generative AI and Language Models in Human Genetics and Health: From Variant Interpretation to Clinical Decision Support.Semantic proximity Read

Synthesize Extremely High-dimensional Longitudinal Electronic Health Records via Hierarchical Autoregressive Language ModelSemantic proximity Read

Diagnostic Performance Comparison between Generative AI and Physicians: A Systematic Review and Meta-AnalysisSemantic proximity Read

Semantic-Constrained Generative Modeling for Health-Care Data Under Distribution ShiftSemantic proximity Read

Leveraging GPT-4 for Identifying Cancer Phenotypes in Electronic Health Records: A Performance Comparison between GPT-4, GPT-3.5-turbo, Flan-T5 and spaCy’s Rule-based & Machine Learning-based methodsSemantic proximity Read