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--- |
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license: cc-by-4.0 |
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language: |
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- en |
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metrics: |
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- f1 |
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- accuracy |
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library_name: transformers |
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pipeline_tag: text-classification |
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--- |
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# lncrna-biocontext |
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This model is designed to determine whether a given abstract talks about an lncRNA in the context of disease or not. |
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The model has been trained on data from [lncBook-Wiki](https://ngdc.cncb.ac.cn/lncbook/) about papers |
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which have been curated by experts based on the biological context they discuss. We have collected the |
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abstracts for these papers and simplified the classification into disease/not disease. We then fine-tune a |
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[longformer](https://huggingface.co/allenai/longformer-base-4096) model to make a binary classification. |
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We achieve pretty good results: |
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| Metric | Score | |
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| Accuracy | 0.84 | |
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| F1 | 0.82 | |
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| ROC| 0.98 | |
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Though the test set is only 59 examples, with 22 discussing disease. |
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The next step will be to be able to classify both the specific disease (e.g. lung adenocarcinoma), and the non-disease |
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context (e.g. localisation) a paper discusses. |
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