E. Andres Rivera-Munoz

Performance Characteristics of Reasoning Large Language Models for Evidence Extraction from Clinical Genomics Literature

This paper evaluates large language models for automated PS4 evidence extraction from clinical genomics literature, finding high accuracy but model-dependent performance.

Improving Automated Deep Phenotyping Through Large Language Models Using Retrieval Augmented Generation

RAG-HPO improves HPO term assignment using retrieval-augmented generation, achieving higher precision and recall than existing tools in phenotypic analysis of clinical text.

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing

The paper develops criteria for identifying, sharing, and reporting novel candidate genes in clinical genomic testing to improve diagnostic yield for Mendelian conditions.