From Text to Translation: Using Language Models to Prioritize Variants for Clinical Review.

ABSTRACT: Despite rapid advances in genomic sequencing, most rare genetic variants remain insufficiently characterized for clinical use, limiting the potential of personalized medicine. When classifying whether a variant is pathogenic, clinical labs adhere to diagnostic guidelines that comprehensively evaluate many forms of evidence including case data, computational predictions, and functional screening. While a substantial amount of clinical evidence has been developed for these variants, the majority cannot be definitively classified as 'pathogenic' or 'benign', and thus persist as 'Variants of Uncertain Significance' (VUS). We processed over 2.4 million plaintext variant summaries from ClinVar, employing sentence-level classification to remove content that does not contain evidence and removing

SUBMITTER: Li W 

PROVIDER: S-EPMC11722495 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature