Author

A. 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· 1 Cell Biology· 1

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

K. Saini· 2 shared A. Tastanova· 1 shared A. Y. Wong-Thai· 1 shared B. Chan· 1 shared C. Chang· 1 shared C. Corona· 1 shared C. Johnson· 1 shared E. A. Ashley· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersCancer Biology

K. Saini

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2 papers

Recent·Most cited

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

E. Lattmann, A. Jovic, J. Kim, T. Pham, C. Corona, Z. Lian, K. Saini, M. Ray, V. Lu, A. Tastanova, S. C. Boutet, M. 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

Realtime morphological characterization and sorting of unlabeled viable cells using deep learning

M. Salek, N. Li, H.-P. Chou, K. Saini, A. Jovic, K. B. Jacobs, C. Johnson, E. J. Lee, C. Chang, P. Nguyen, J. Mei, K. P. Pant, A. Y. Wong-Thai, Q. F. Smith, S. Huang, , M. Masaeli

COSMOS enables real-time, unlabeled cell sorting based on morphology using deep learning, achieving high enrichment of viable cells for functional analysis.

bioRxiv · Feb 28, 2022 · PreprintCell Biology