Author

Sarah E. Carlson

Virginia EnergyORCID 0009-0003-1410-5890Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:polygenic risk· 1 Approach:statistical model· 1

Frequent Co-Authors

Carlos CruchagaiD· 1 shared Ellen McRae GreytakiD· 1 shared James O’Connor· 1 shared Janet Cady· 1 shared Stephen Hermes· 1 shared Steven L. Armentrout· 1 shared The Alzheimer’s Disease Neuroimaging Initiative· 1 shared Thomas S. WingoiD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperGenetic & Genomic Medicine

Carlos CruchagaORCID

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

Genetic & Genomic MedicinemedRxivPreprintFeb 10, 2023

Epistatic Features and Machine Learning Improve Alzheimer's Risk Prediction Over Polygenic Risk Scores

Stephen Hermes, Janet Cady, Steven L. Armentrout…·The Alzheimer’s Disease Neuroimaging Initiative

This study develops a paragenic risk score that improves Alzheimer's disease risk prediction by incorporating epistatic interactions and machine learning, outperforming traditional polygenic risk scores.

3 citations

humanGWAS summary statistics

𝕏 PostBluesky