Bayer-Group/text-to-sql-epi-ehr-naacl2024
Code for Retrieval augmented text-to-SQL generation for epidemiological question answering using electronic health records
This tool helps epidemiologists, medical researchers, and public health analysts quickly extract insights from large electronic health records (EHR) datasets. You provide a question in plain English, like "How many women have atopic dermatitis?", and it generates a SQL query. This query can then be executed against an OMOP-CDM compliant database to retrieve the relevant patient counts or data.
No commits in the last 6 months.
Use this if you need to translate natural language questions into precise SQL queries for epidemiological analysis of electronic health records, especially within the OMOP Common Data Model.
Not ideal if you don't work with electronic health records in an OMOP-CDM format or if you need a fully automated query execution system without any manual review or adjustment.
Stars
24
Forks
7
Language
Python
License
MIT
Category
Last pushed
May 15, 2024
Commits (30d)
0
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curl "https://pt-edge.onrender.com/api/v1/quality/rag/Bayer-Group/text-to-sql-epi-ehr-naacl2024"
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