PyCVDRisk
importedsoftware/pycvdrisk
a comprehensive Python package for cardiovascular disease risk prediction, implementing 46 validated models
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- pycvdrisk.aljasem.eu.org
- Repository
- github.com/m-aljasem/PyCVDRisk
- Documentation
- unknown
- Tags
- cardiology · prevention · risk-assessment
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- t2dmriskeqnsprevention
Updated risk equations for type 2 diabetes complications
- biopsycardiology
Python package for preprocessing OpenSlide image files and their corresponding annotations for use with Machine Learning segmentation models.
- BRAVEHEARTcardiology
BRAVEHEART: Open-source software for automated electrocardiographic and vectorcardiographic analysis
- cinc-challenge2017cardiology
ECG classification from short single lead segments (Computing in Cardiology Challenge 2017 entry)
- DeepCardiologycardiology
Implementations of deep and other ML approaches for cardiology.
- dynamiccardiology
EchoNet-Dynamic is a deep learning model for assessing cardiac function in echocardiogram videos.
- api.github.com/repos/m-aljasem/PyCVDRiskretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2025-12-10, 3 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/38.json→ .entries["pycvdrisk"]
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