Text mining for precision medicine: automating disease-mutation relationship extraction from biomedical literature
Conclusions The proposed approach improves the state of the art for mutation-disease extraction from text. It is scalable and generalizable to identify mutations for any disease at a PubMed scale.
Source: Journal of the American Medical Informatics Association - Category: Information Technology Authors: Singhal, A., Simmons, M., Lu, Z. Tags: Research and Applications Source Type: research
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