Text Classification
Transformers
PyTorch
TensorFlow
Safetensors
English
bert
medical
clinical
assertion
negation
Instructions to use bvanaken/clinical-assertion-negation-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bvanaken/clinical-assertion-negation-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bvanaken/clinical-assertion-negation-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bvanaken/clinical-assertion-negation-bert") model = AutoModelForSequenceClassification.from_pretrained("bvanaken/clinical-assertion-negation-bert") - Inference
- Notebooks
- Google Colab
- Kaggle
Failed couple of times on the text provided.
#4
by alsayedm - opened
E.g failed on:
- 'came back with increase sob, no fever. did not take [entity] voriconazole [entity] as saying not given on discharge'
- 'cf bronchiectasis with recurrent admissions.recently discharged. he dnar with intervention came back with increase sob, no [entity] fever [entity]. did not take voriconazole as saying not given on discharge. although prescribed in the system. crp and procal high.'
shows as present.