Author

Elizabeth C. Lee

Johns Hopkins UniversityORCID 0000-0002-4156-9637Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Assay:imaging· 1 Organism:mouse· 1

Frequent Co-Authors

Ariel Lubonja· 1 shared Bowen LiiD· 1 shared Hang YuiD· 1 shared Luciana Ribeiro DinisiD· 1 shared Nattawat ChaiyawongiD· 1 shared Opeoluwa Adewale-Fasoro· 1 shared Prakash SrinivasaniD· 1 shared Ravi Kumar NarayanasamyiD· 1 shared

Activity by Year

2024-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperMicrobiology

Ariel Lubonja

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1 paper

Recent·Most cited

Application of machine learning in a rodent malaria model for rapid, accurate, and consistent parasite counts

Sean A. Yanik, Hang Yu, Nattawat Chaiyawong, Opeoluwa Adewale-Fasoro, Luciana Ribeiro Dinis, Ravi Kumar Narayanasamy, Elizabeth C. Lee, Ariel Lubonja, Bowen Li, Stefan Jaeger, Prakash Srinivasan

The paper develops a machine learning tool for automated parasite counting in rodent malaria models, achieving high accuracy and consistency across labs.

American Journal of Tropical Medicine and Hygiene · Sep 10, 2024Peer-reviewedMicrobiology