coronaryarteries
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
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✓codemeta.json file
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✓.zenodo.json file
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○DOI references
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○Academic publication links
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○Scientific vocabulary similarity
Low similarity (3.5%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: MiriamCobo
- License: apache-2.0
- Language: Jupyter Notebook
- Default Branch: master
- Size: 42.6 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Artificial intelligence to detect coronary artery tortuosity through
coronary angiography
Author: Miriam Cobo (CSIC)
Description: This work provides a tool to detect coronary artery tortuosity in coronary angiography.
Acknowledgements: Miriam Cobo acknowledges support from Consejo Superior de Investigaciones Científicas (CSIC) and Institute of Physics of Cantabria (IFCA) given by the European Commission – NextGenerationEU, through CSIC’s Global Health Platform (“PTI Salud Global”).
This work is an adaptation of the original image classification DEEP Hybrid-DataCloud project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 777435 developed by Ignacio Heredia (CSIC). You can find more information about it in the DEEP Marketplace.
Owner
- Name: Miriam Cobo
- Login: MiriamCobo
- Kind: user
- Location: IFCA
- Company: CSIC
- Website: cobocano@ifca.unican.es
- Repositories: 2
- Profile: https://github.com/MiriamCobo
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Cobo Cano" given-names: "Miriam" orcid: " https://orcid.org/ 0000-0001-9208-9062" title: "Coronary artery tortuosity detection tohrough coronary artery project software" version: 1.0.0 doi: date-released: 2022-08-04 url: "https://github.com/MiriamCobo/CoronaryArteries.git"
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Dependencies
- Flask >=1.0.2
- Jinja2 >=2.10
- PyYAML >=3.12
- Sphinx *
- aiohttp >=3.6.2
- albumentations ==0.1.8
- deepaas >=1.0.0
- gunicorn >=19.9.0
- matplotlib >=2.2.2
- numpy >=1.14.5
- opencv-python >=3.4.1.4
- python-dotenv >=0.5.1
- requests >=2.18.4
- scikit-learn >=0.19.1
- seaborn >=0.8.1
- tensorboardX >=1.4
- tqdm >=4.25.0
- webargs >=5.5.2,<6.0.0
- flake8 * test
- pylint * test