Article

Infrastructure for synthetic health data

2023-07-22

Abstract excerpt

<p>Machine learning (ML) methods are becoming ever more prevalent across all domains of lifesciences. However, a key component of effective ML is the availability of large datasets thatare diverse and representative. In the context of health systems, with significant heterogeneityof clinical phenotypes and diversity of healthcare systems, there exists a necessity to developand refine unbiased and fair ML models. S...

Topics

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

Identifiers and source

Literature Corpus work: c9653040-f168-5b17-9b22-256c280f0011
DOI: 10.37044/osf.io/q4zgx

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Infrastructure for synthetic health dataDOI 10.37044/osf.io/q4zgxRead

Synthetic data for privacy-preserving clinical risk predictionSemantic proximity Read

Actionability of Synthetic Data in a Heterogeneous and Rare Healthcare Demographic; Adolescents and Young Adults (AYAs) with CancerSemantic proximity Read

Generating synthetic electronic health record data: a methodological scoping review with benchmarking on phenotype data and open-source software.Semantic proximity Read

SynthCraft: an AI partner for synthetic data generation to support data access and augmentation in healthcareSemantic proximity Read

Mending Synthetic Healthcare Data with MAPS: Model Agnostic Post-hoc Synthetic Data Refinement FrameworkSemantic proximity Read

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

Exploring the Role of Synthetic Data in the Future of AI in Healthcare: Frameworks, Challenges, and ImplicationsSemantic proximity Read

Evaluation of AI-Generated Synthetic Data for Clinical Research in Secondary Cardiovascular Prevention among Dyslipidemia PatientsSemantic proximity Read

Synthetic data generation for a longitudinal cohort study – evaluation, method extension and reproduction of published data analysis resultsSemantic proximity Read

Data Quality Verification Metrics in Medicine: Experiments and Evaluations from the Perspectives of Safety and UtilitySemantic proximity Read

On the evaluation of synthetic longitudinal electronic health recordsSemantic proximity Read

Synthesising artificial patient-level data for Open Science - an evaluation of five methodsSemantic proximity Read