| # PD Cognition BioClinicalBERT Fine Tuned spaCy Model |
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| This model is a spaCy pipeline for span categorization trained on clinical text related to Parkinson disease cognition. It uses BioClinicalBERT as the transformer backbone and predicts labeled spans stored under the key sc. |
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| ## Model Details |
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| Base model emilyalsentzer Bio ClinicalBERT |
| Framework spaCy with spacy transformers |
| Task span categorization |
| Language English |
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| ## Labels |
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| The label set is defined in labels.json included in the model directory. |
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| ## Input: |
| Raw clinical text string |
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| ## Output: |
| Predicted spans in doc.spans["sc"] with start end label and score |
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| ## Usage |
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| ```python |
| import spacy |
| |
| nlp = spacy.load("path_to_model_best") |
| doc = nlp("Patient shows cognitive decline and memory impairment") |
| |
| for span in doc.spans["sc"]: |
| print(span.text, span.label_, span.score) |
| ``` |
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| ## Files |
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| model best spaCy pipeline |
| config cfg training configuration |
| meta json pipeline metadata |
| labels json list of span labels |
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| ## Notes |
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| This is a spaCy model and should be loaded with spacy.load not transformers |
| Performance depends on span alignment and threshold tuning |
| Intended for research use on clinical text |
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| ## Citation |
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| ```bibtex |
| @article{khanna2024cognitive, |
| title={Toward Automated Cognitive Assessment in Parkinson’s Disease Using Pretrained Language Models}, |
| author={Khanna, Varada and Bhatt, Nilay and Shin, Ikgyu and Rosso, Mattia and Tinaz, Sule and Ren, Yang and Xu, Hua and Keloth, Vipina K}, |
| journal={arXiv preprint arXiv:2511.08806}, |
| year={2025} |
| } |
| ``` |
