ritaranx/ClinGen
[ACL 2024 Findings] This is the code for our paper "Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models".
This project helps medical researchers and clinical NLP practitioners create high-quality synthetic training data for various clinical text tasks. You provide an OpenAI API key and specify your desired clinical dataset; the output is a synthetic training dataset generated with incorporated medical knowledge, ready for use in machine learning models. This resource is for those working with clinical notes, research papers, or patient information who need to augment limited real-world data.
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Use this if you need to generate realistic, knowledge-infused synthetic training data to improve the performance of your clinical natural language processing models.
Not ideal if you are looking for an off-the-shelf model or an application to directly analyze clinical text without involving further model training.
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41
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Language
Python
License
MIT
Category
Last pushed
Jun 23, 2024
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Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/prompt-engineering/ritaranx/ClinGen"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.