Author

Hope Twede

Microsoft (United States)ORCID 0000-0002-6814-4532Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:GWAS summary statistics· 1 Organism:human· 1

Frequent Co-Authors

Alex Bloemendal· 1 shared Amanda K. HalliD· 1 shared Ashley Mae ConardiD· 1 shared Cas SimonsiD· 1 shared Christina Anne Austin-TseiD· 1 shared Daniel G. MacArthuriD· 1 shared Emily O’HeiriD· 1 shared Greg Smith· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperGenomics

Alex Bloemendal

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1 paper

Recent·Most cited

The Evidence Aggregator: AI reasoning applied to rare disease diagnostics

Hope Twede, Lynn S. Pais, Samantha J. Bryen, Emily O’Heir, Greg Smith, Ron Paulsen, Christina Anne Austin-Tse, Alex Bloemendal, Cas Simons, Amanda K. Hall, Scott Saponas, Jeremiah D. Wander, Daniel G. MacArthur, Heidi L. Rehm, Ashley Mae Conard

The Evidence Aggregator (EvAgg) uses generative AI to streamline rare disease diagnostics by extracting and summarizing genetic variant and clinical information from literature, improving efficiency and accuracy.

Genetics in Medicine · May 27, 2026Peer-reviewedGenomics