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                <identifier>oai:data.mendeley.com/tkwzysr4y6.6</identifier>
                <datestamp>2023-10-25T15:26:58Z</datestamp>
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    <dc:creator>Chen, Robert</dc:creator>
    <dc:title>Prediction of Venous Thromboembolism in Diverse Populations Using Machine Learning and Electronic Health Records</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>Contains resources needed to train, test, and analyze performance of gradient boosting models used to predict venous thromboembolism (VTE) from electronic health record (EHR) data.

&quot;Code for analyses&quot; folder: Contains code we used for the analyses in our paper.
Prediction.ipynb: Contains code needed to run trained models.
Small, Medium, and Large.xlsx: Excel templates to correctly format data for prediction generation.
Models.zip: Contains trained models. Note that this is 0.4 GB once unzipped.
Analysis.ipynb: Contains code used to train the models.

Dependencies: Python 3.10.9; Pandas 1.5.1; LightGBM 3.3.2.</dc:description>
    <dc:subject>Machine Learning</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/tkwzysr4y6.6</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/tkwzysr4y6.6</dc:identifier>
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    <dc:date>2023-10-25T15:26:58Z</dc:date>
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