Add dataset README
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README.md
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# MedText-Clinical-Processed
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<p align="left">
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📑 <a href="https://arxiv.org/papers/xxxx.xxxxx" target="_blank">Paper</a>    |    🌐 <a href="https://medtext.github.io/" target="_blank">Project Page</a>    |    💾 <a href="https://huggingface.co/collections/toolevalxm/medtext-collection" target="_blank">Released Resources</a>    |    📦 <a href="https://github.com/xmhtoolathlon/MedText-DataHub" target="_blank">Repo</a>
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This is the processed version of MedText-Clinical dataset, containing structured medical entities and relations extracted using BiomedBERT-Large.
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**Dataset**
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<table>
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<tr>
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<th>Dataset</th>
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<th>Link</th>
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</tr>
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<tr>
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<td>MedText-Clinical-Processed</td>
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<td style="background-color: #e6f3ff; text-align: center; vertical-align: middle;">
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<a href="https://huggingface.co/datasets/toolevalxm/MedText-Clinical-Processed">🤗</a>
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</td>
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</tr>
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</table>
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Please also check the raw data: [toolevalxm/MedText-Clinical-Raw](https://huggingface.co/datasets/toolevalxm/MedText-Clinical-Raw).
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**Models Used**
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- BiomedBERT-Large for entity extraction
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- Clinical-Longformer for relation classification
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**Introduction**
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We use a pipeline approach combining BiomedBERT-Large for named entity recognition and Clinical-Longformer for relation extraction. The processing extracts medical concepts (diseases, medications, procedures) and their relationships from raw clinical notes.
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*Due to licensing requirements, we only release the de-identified subset of the full dataset.
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