autonlab/KeyClass

Code for "Classifying Unstructured Clinical Notes via Automatic Weak Supervision", MLHC 2022.

39
/ 100
Emerging

KeyClass helps categorize large volumes of unstructured text, like clinical notes or customer reviews, when you don't have existing labeled examples. You provide descriptions of the categories you want to use, and KeyClass automatically assigns labels to your documents. This is ideal for researchers, analysts, or anyone who needs to quickly sort and understand vast amounts of text data without manual labeling.

No commits in the last 6 months.

Use this if you need to classify text documents into categories but lack human-labeled examples and want to avoid the time and cost of manual annotation.

Not ideal if you already have a well-labeled dataset for your text classification task, as traditional supervised methods might be more straightforward.

clinical-note-analysis document-categorization text-analytics data-mining content-moderation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 17 / 25

How are scores calculated?

Stars

16

Forks

8

Language

Python

License

MIT

Last pushed

Mar 10, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/autonlab/KeyClass"

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