sicdb-meds
The Salzburg Intensive Care database (SICdb) MEDS ETL.
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: nature.com, zenodo.org -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.6%) to scientific vocabulary
Repository
The Salzburg Intensive Care database (SICdb) MEDS ETL.
Basic Info
Statistics
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 2
Metadata Files
README.md
SICdb_MEDS ETL
The SICdb dataset offers insights into over 27 thousand intensive care admissions, including therapies and data on preceding surgeries. Data were collected between 2013 and 2021 from four different intensive care units at the University Hospital Salzburg, having more than 3 thousand intensive care admissions per year on 41 beds. The dataset is deidentified and contains, amongst others, case information, vital signs, laboratory results and medication data. SICdb provides both aggregated once-per-hour and highly granular once-per-minute data, making it suitable for computational and machine learning-based research. (source: https://www.sicdb.com/Documentation/Main_Page)
Usage
```bash pip install SICdb_MEDS # you can do this locally or via PyPI
Download your data or set download credentials
MEDSextract-SICdb rootoutputdir=$ROOTOUTPUT_DIR
or, if you have the data already downloaded
MEDSextract-SICdb rootoutputdir=$ROOTOUTPUTDIR dodownload=False
or, if you want enable waveform extraction and processing (takes significantly longer and up to 100GB of RAM)
MEDSextract-SICdb rootoutputdir=$ROOTOUTPUTDIR doprocess_waveform=True ```
Citation
If you use this dataset, please cite the original publication below and the ETL (see cite this repository):
```
@article{rodemundHarnessingBigData2024, title = {Harnessing {Big} {Data} in {Critical} {Care}: {Exploring} a new {European} {Dataset}}, volume = {11}, copyright = {2024 The Author(s)}, issn = {2052-4463}, shorttitle = {Harnessing {Big} {Data} in {Critical} {Care}}, url = {https://www.nature.com/articles/s41597-024-03164-9}, doi = {10.1038/s41597-024-03164-9}, language = {en}, number = {1}, urldate = {2024-04-04}, journal = {Scientific Data}, author = {Rodemund, Niklas and Wernly, Bernhard and Jung, Christian and Cozowicz, Crispiana and Koköfer, Andreas}, month = mar, year = {2024}, note = {Publisher: Nature Publishing Group}, keywords = {Clinical trial design, Experimental models of disease}, pages = {320}, }
```
Owner
- Name: Robin van de Water
- Login: rvandewater
- Kind: user
- Location: Berlin
- Company: Hasso Plattner Institute
- Website: https://www.rpvandewater.com/
- Repositories: 1
- Profile: https://github.com/rvandewater
PhD student in Medical Event Prediction at Hasso Plattner Institute in collaboration with the Charité hospital (Berlin)
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "SICdb_MEDS ETL"
version: "0.0.1"
doi: "10.5281/zenodo.14893939"
authors:
- family-names: "van de Water"
given-names: "Robin Philippus"
orcid: "https://orcid.org/0000-0002-2895-4872"
date-released: "2025-02-19"
url: "https://github.com/rvandewater/SICdb_MEDS"
repository-code: "https://github.com/rvandewater/SICdb_MEDS"
license: "MIT"
GitHub Events
Total
- Release event: 2
- Watch event: 2
- Public event: 1
- Push event: 7
- Create event: 2
Last Year
- Release event: 2
- Watch event: 2
- Public event: 1
- Push event: 7
- Create event: 2
Committers
Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Robin van de Water | r****r@g****m | 21 |
Issues and Pull Requests
Last synced: 9 months ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 11 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
- Total maintainers: 1
pypi.org: sicdb-meds
A template ETL pipeline to extract arbitrary data into the MEDS format.
- Homepage: https://github.com/rvandewater/SICdb_MEDS
- Documentation: https://sicdb-meds.readthedocs.io/
- License: MIT License
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Latest release: 0.0.2
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout v4 composite
- actions/setup-python v5 composite
- pre-commit/action v3.0.1 composite
- actions/checkout v4 composite
- actions/setup-python v5 composite
- pre-commit/action v3.0.1 composite
- trilom/file-changes-action v1.2.4 composite
- actions/checkout v4 composite
- actions/download-artifact v4 composite
- actions/setup-python v5 composite
- actions/upload-artifact v4 composite
- pypa/gh-action-pypi-publish release/v1 composite
- sigstore/gh-action-sigstore-python v3.0.0 composite
- actions/checkout v4 composite
- actions/setup-python v5 composite
- codecov/codecov-action v4.0.1 composite
- codecov/test-results-action v1 composite
- beautifulsoup4 *
- hydra-core *
- loguru *
- meds-transforms >=0.1
- requests *