VectorInstitute/cyclops

A toolkit for evaluating and monitoring AI models in clinical settings

52
/ 100
Established

This toolkit helps clinical researchers and healthcare practitioners develop, evaluate, and monitor AI models for medical applications. You can input various clinical data types like images, time-series, or tabular data, and it outputs model evaluations, performance metrics, and detailed model report cards. It's designed for professionals who build and deploy machine learning solutions in healthcare settings.

Use this if you are developing or deploying AI models for clinical prediction tasks and need robust tools for data preparation, model evaluation, and continuous monitoring for shifts in real-world clinical data.

Not ideal if your primary focus is on foundational AI research outside of healthcare or if you require highly specialized statistical analysis tools not directly related to ML model performance.

clinical-AI medical-imaging healthcare-analytics predictive-medicine model-monitoring
No Package No Dependents
Maintenance 10 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 17 / 25

How are scores calculated?

Stars

89

Forks

16

Language

Python

License

Last pushed

Mar 09, 2026

Commits (30d)

0

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