iamb
Bnlearn's IAMB algorithm using DAGs for medical risk assessment to let NASA HSRB formalize a shared causal flow of risk model among Risk Board stakeholders. Validating the DAG connections by populating them with empirical biological data from the NASA Open Science Data Repository.
Science Score: 44.0%
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
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○Academic publication links
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (1.6%) to scientific vocabulary
Last synced: 10 months ago
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Bnlearn's IAMB algorithm using DAGs for medical risk assessment to let NASA HSRB formalize a shared causal flow of risk model among Risk Board stakeholders. Validating the DAG connections by populating them with empirical biological data from the NASA Open Science Data Repository.
Basic Info
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- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Created almost 3 years ago
· Last pushed over 2 years ago
Metadata Files
Readme
License
Citation
README.md
DAG ML: IAMB
Owner
- Name: dag-ml
- Login: dag-ml
- Kind: organization
- Repositories: 1
- Profile: https://github.com/dag-ml
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Doan" given-names: "Jasper" orcid: "https://orcid.org/0000-0000-0000-0000" title: "iamb" version: 1.0.0 doi: 10.5281/zenodo.1234 date-released: 2023-09-29 url: "https://github.com/dag-ml/iamb"
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- Watch event: 1