Synthetic Electronic Health Record data generated at UCLH for the project : AI Septron

DOI

Synthetic data generated to represent the structure of data extracted from the UCLH Electronic Health Record. They are selected tables and fields from the OMOP Common Data Model v5.4 with concept_name columns added for readability.These synthetic data are based on the AI Septron project that aims to make a strong and accurate computer program that can identify the risk of sepsis and serious infections in children. AI Septron is run by Dr Sylvester Gomes a Consultant in Paediatric Emergency Medicine at Evelina London Children's Hospital.These are low fidelity synthetic data generated using datafaker. The columns are currently generated independently so any relationships between them may be nonsensical e.g. birth dates occurring after death dates.These data are artificially generated, any resemblance to real patients is coincidental.

Identifier
DOI https://doi.org/10.5522/04/29581715.v1
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Provenance
Creator South, Andy; Piatek, Stefan
Publisher University College London UCL
Contributor Figshare
Publication Year 2025
Rights https://creativecommons.org/publicdomain/zero/1.0/
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Dataset
Discipline Other