Author

Andreja Jovic

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2 Assay:scRNA-seq· 1

Frequent Co-Authors

Christian Corona· 2 shared Evelyn LattmanniD· 2 shared Kiran Saini· 2 shared Manisha Ray· 2 shared Mitchell Paul LevesqueiD· 2 shared Stéphane C. Boutet· 2 shared Tiffine PhamiD· 2 shared Zhouyang LianiD· 2 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 44 mutual co-author links

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2 shared papersCancer Biology

Christian Corona

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2 papers

Recent·Most cited

Deep learning-driven morphology analysis enables label-free classification of therapeutic agent- naive versus resistant cancer cells

Cyril Y. Ramathal, Kiran Saini, Zhouyang Lian, Christian Corona, Tiffine Pham, Ryan Carelli, Stéphane C. Boutet, Manisha Ray, Sunantha Sethuraman, Vivian Prindle, Evelyn Lattmann, Maria-Grazia Molvetti, Andreas Dzung, Mitchell Paul Levesque, Matt Barnes, Andreja Jovic

This study uses deep learning to classify drug-naive and resistant cancer cells based on morphology, achieving high accuracy across multiple cancer types and drug classes.

bioRxiv · Jan 22, 2025 · PreprintCancer Biology

Label-Free Melanoma Phenotype Classification Using Artificial Intelligence-Based Morphological Profiling

Evelyn Lattmann, Andreja Jovic, Julie J. Kim, Tiffine Pham, Christian Corona, Zhouyang Lian, Kiran Saini, Manisha Ray, Vivian Lu, Aizhan Tastanova, Stéphane C. Boutet, Mitchell P. Levesque

This paper develops an AI-based classifier to classify melanoma cell phenotypes using morphology, validated by scRNA-Seq, showing morphology correlates with phenotypic states.

bioRxiv · Jun 28, 2024 · PreprintCancer Biology