'[object Object]': null
license: apache-2.0
language:
- en
library_name: transformers
tags:
- medical
widget:
- text: >-
Patient is a a formerly incarcerated individual having arrived in the ED
with stomach pain.
- example_title: Former Incarceration
- text: Patient arrived in the ED for chest pain.
- example_title: No Incarceration
Model Card for incar-status-any
A Clinical Longformer-based model trained by the HAIL lab to predict incarceration status (past and present) in ED Notes.
Model Details
Model Description
- Developed by: Vimig Socrates
- Model type: Longformer
- Language(s) (NLP): English
- License: Apache License 2.0
- Finetuned from model: Clinical Lonformer
Uses
This model can be used to predict the incarceration status that a patient might have given most types of clinical ED notes.
Bias, Risks, and Limitations
This should not be used directly without supervision from a physician as predicting incarceration status incorrectly can have significant negative social and clinical impacts.
Training Details
Training Data
This model was trained on custom annotated data labeled for incarceration status from Yale-New Haven Health Hospital System ED Notes.
Training Procedure
Evaluation
TODO
Testing Data, Factors & Metrics
Results
TODO
]
Citation [optional]
Coming soon!
BibTeX:
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APA:
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Model Card Authors [optional]
Vimig Socrates
Model Card Contact
Vimig Socrates: vimig.socrates@yale.edu