YalaLab/rate

A Python-based engine for processing radiology reports using the Qwen3 model with sglang for efficient batch inference. Includes quality control file generation and performance evaluation tools for comprehensive validation workflows with debug mode for faster iteration.

35
/ 100
Emerging

This tool helps radiologists and clinical researchers efficiently process large volumes of radiology reports. It takes raw radiology reports in a CSV file and extracts key information such as findings, categorized data, and answers to specific questions about the report content. The output is structured data that can be used for analysis or quality control.

Use this if you need to systematically extract and categorize clinical findings and other specific information from a large collection of radiology reports.

Not ideal if you need real-time analysis of individual reports or are not working with large batches of textual radiology data.

radiology-workflow clinical-text-analysis medical-report-processing healthcare-data-extraction
No Package No Dependents
Maintenance 6 / 25
Adoption 5 / 25
Maturity 13 / 25
Community 11 / 25

How are scores calculated?

Stars

12

Forks

2

Language

Python

License

Last pushed

Nov 20, 2025

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/rag/YalaLab/rate"

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