Generated Patient Data for ARDS Model Training

DOI

Patient data that was populated as follows: The statistical distribution of curated data from the MIMIC-III dataset. Data based on these distributions was generated for 19 parameters. The data generated for these parameters was fed into a virtual patient model to predict a further 4 parameters: PaO2, PaCO2, pH, and HCO3. The outputs from the virtual patient was appended to the original generated data and can be used to train neural networks as inputs and expected outputs.

Identifier
DOI https://doi.org/10.23728/b2share.b143c287bb69482a90ababe7a5a8eb4a
Source https://b2share.eudat.eu/records/b143c287bb69482a90ababe7a5a8eb4a
Metadata Access https://b2share.eudat.eu/api/oai2d?verb=GetRecord&metadataPrefix=eudatcore&identifier=oai:b2share.eudat.eu:b2rec/b143c287bb69482a90ababe7a5a8eb4a
Provenance
Creator Barakat, Chadi
Publisher EUDAT B2SHARE
Publication Year 2023
Rights Creative Commons Attribution (CC-BY); info:eu-repo/semantics/openAccess
OpenAccess true
Contact c.barakat(at)fz-juelich.de
Representation
Format csv
Size 374.7 MB; 1 file
Discipline 4.1.5 → Computer sciences → Data structures; 5.13.4 → Medicine → Health informatics