Author

V. Lu

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 Pathology· 1

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

J. Kim· 2 shared K. Saini· 2 shared S. C. Boutet· 2 shared Z. Lian· 2 shared A. Jovic· 1 shared A. Mavropoulos· 1 shared A. Tastanova· 1 shared A. Wong-Thai· 1 shared

Activity by Year

2023-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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2 shared papersCancer Biology

J. Kim

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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

Artificial intelligence-driven morphology-based enrichment of malignant cells from body fluid

A. Mavropoulos, C. Johnson, V. Lu, J. Nieto, E. Schneider, K. Saini, M. L. Phelan, L. Hsie, M. Wang, J. Cruz, J. Mei, J. Kim, Z. Lian, N. Li, S. C. Boutet, , J. Rao

This study uses deep learning and microfluidic sorting to enrich malignant cells from body fluids, improving detection of tumor fractions and mutations.

bioRxiv · Jan 24, 2023Pathology