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KGRD: a knowledge-graph-augmented automated reasoning framework for diagnosis and counselling of paediatric rare genetic disorders
Abstract Diagnosis and counselling for paediatric rare diseases remain constrained by the sparsity of structured patient-level data and fragmented genetic knowledge, which can induce ‘common-attention’ bias in conventional large language models (LLMs). Here, we describe KGRD, a knowledge-graph-augmented diagnostic support framework empowered by knowledge-driven and data-driven inference over patient-level genomic and phenotypic data.
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