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New Arabic Medical Dataset for Diseases Classification

arXiv 2106.15236 ↗First posted 29 Jun 2021cs.CLcited by 0

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Abstract (arXiv)

The Arabic language suffers from a great shortage of datasets suitable for training deep learning models, and the existing ones include general non-specialized classifications. In this work, we introduce a new Arab medical dataset, which includes two thousand medical documents collected from several Arabic medical websites, in addition to the Arab Medical Encyclopedia. The dataset was built for the task of classifying texts and includes 10 classes (Blood, Bone, Cardiovascular, Ear, Endocrine, Eye, Gastrointestinal, Immune, Liver and Nephrological) diseases. Experiments on the dataset were performed by fine-tuning three pre-trained models: BERT from Google, Arabert that based on BERT with large Arabic corpus, and AraBioNER that based on Arabert with Arabic medical corpus.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 51 references that are in the map. First posted on arXiv 29 Jun 2021.

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References · 19

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7 more
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