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imperiumhf/imp_clinical_dxcode_ner_v2
imp_clinical_dxcode_ner_v2 is a token classification model from imperiumhf. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
This model is designed for the identification of tokens related to ICD-10 DX codes in clinical documents. We focus on a subset of approximately 4,000+ codes, which are the most frequently used in clinical documentatio…
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From the Hugging Face model README
This model is designed for the identification of tokens related to ICD-10 DX codes in clinical documents. We focus on a subset of approximately 4,000+ codes, which are the most frequently used in clinical documentation. Please refer config.json file for target codes we used to train this model.
The dataset comprises clinical documents annotated for ICD-10 DX codes. We ensure a balanced representation of the selected codes to prevent model bias. the dataset is private one, used internally to trian the model.
Due to GPU memory constraints, training is conducted in epochs with periodic evaluations to monitor performance and mitigate overfitting.
from transformers import pipeline
pipe = pipeline("token-classification", model="imperiumhf/imp_clinical_dxcode_ner_v2")
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All the rights over this model is reserved for Imperium software solutions pvt ltd.