P604: Evaluating AI-assisted phenotyping for variant prioritization in clinical laboratory genome/exome workflows

Genetics in Medicine Open 2026 Open access

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Authors: Sarah Barnett, Anna A. Essendrup, Kristen J. Rasmussen, Nicole J. Boczek, Cherisse A. Marcou, Kyna A. Byerly, Elaine White, Carlos Garcia Arredondo, Piyush Mukherjee, Abdülkadir Albayrak, Yao Xiao (227567), Steven Hart
+1 more E. B. Klee
DOI: 10.1016/j.gimo.2026.104095
Cited by: 0

Abstract

For exome and genome sequencing, accurate phenotypic representation is critical for variant prioritization in genomic analysis. While clinical summaries and HPO terms are traditionally generated manually, this is a time-consuming and subjective process. Emerging artificial intelligence (AI) tools offer automated alternatives. GOATT (genomic optimization and appropriateness of testing tool), a lab-developed tool, utilizes generative AI with custom prompting and a proprietary HPO extraction method to interface with the electronic medical record system and streamline this process.

Fields of Study & Subjects

Genomics and Rare Diseases Artificial Intelligence in Healthcare and Education Biomedical Text Mining and Ontologies

Publication details

Journal / source
Genetics in Medicine Open
Volume
4
Pages
104095–104095
Publication date
1 January 2026
Language
EN