kevihiiin/EHR-Indication-Processing

Code for the paper: Transformers and large language models are efficient feature extractors for electronic health record studies

/ 100

Experimental

No License No Package No Dependents

Maintenance 13 / 25

Adoption 3 / 25

Maturity 1 / 25

Community 0 / 25

Stars

Forks

—

Language

Jupyter Notebook

License

—

Category

Last pushed

Mar 10, 2026

Commits (30d)

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/kevihiiin/EHR-Indication-Processing"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

Tencent/PatrickStar

PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP and democratizes AI for everyone.

OpenMotionLab/MotionGPT

[NeurIPS 2023] MotionGPT: Human Motion as a Foreign Language, a unified motion-language...

OpenMotionLab/MotionGPT3

MotionGPT3: Human Motion as a Second Modality, a MoT-based framework for unified motion...

YerbaPage/DetectCodeGPT

Detection of LLM-Generated Codes [ICSE2025]

RobbenRibery/TuoTuo

TuoTuo is a Topic Modeling library for Researchers and Engineers