Examining Rare Disease Biology With Natural Language Processing Text Mining At Takeda

3 Pages

Explains how Takeda applied Linguamatics NLP to enhance its Hunter Outcome Survey registry for Hunter syndrome. NLP extracted genotype–phenotype associations from 461 publications, yielding 380 unique IDS gene mutations with >95% precision and recall. This enriched the registry’s dataset, improved understanding of disease biology, and highlighted risk factors for severe phenotypes. Automating extraction reduced manual workload and provided stakeholders with more comprehensive, accurate rare disease insights.

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Examining Rare Disease Biology With Natural Language Processing Text Mining At Takeda

Examining Rare Disease Biology With Natural Language Processing Text Mining At Takeda

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