COVID 19 therapy target discovery with context aware literature mining

The abundance of literature related to the widespread COVID-19 pandemic is beyond manual inspection of a single expert . We propose a novel embedding generation technique that leverages SciBERT language model pretrained on a large multi-domain corpus of scientific publications and fine-tuned for domain adaptation on the CORD-19 dataset . The conducted manual evaluation by the medical expert and the quantitative evaluation based on therapy targets identified in the related work suggest that the proposed method can be successfully employed for COV-19 therapy target discovery and that it outperforms the baseline FastText method by a large margin . The proposed method is based on the results of a study conducted by a medical expert on how to identify therapy targets that were identified in related work . The method outperforms FastText by a small margin .

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Keywords : therapy - method - related - expert - evaluation -

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