Mapping Synthea CSV to i2b2 with ML-based 14-day Readmission Prediction

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Philipp Grewatta, Tolga Daniel Dittrich, Luisa Vivienne Renner, Victoria M. Lampkemeyer
DOI: 10.5281/zenodo.18562424
Cited by: 0

Abstract

This dataset contains the archived artifacts of a student project on data management and archival concepts.It includes ETL pipelines, mapping rules from Synthea CSV to the i2b2 data warehouse model, data quality checks, and a machine learning pipeline for 14-day hospital readmission prediction. The data is based on synthetic Synthea demo data and does not contain real patient information.

Fields of Study & Subjects

Machine Learning in Healthcare Artificial Intelligence in Healthcare Electronic Health Records Systems

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 February 2026
Language
EN
Document type
Dataset