Author

M. Lisovsky

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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Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:benchmarking· 2 Assay:imaging· 2 Approach:statistical model· 2 Approach:Bayesian inference· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:contrastive learning· 1

Frequent Co-Authors

B. Christensen· 4 shared B. Ren· 4 shared J. Levy· 4 shared N. Azizgolshani· 4 shared X. Liu· 4 shared C. A. Bobak· 3 shared J. O'Malley· 3 shared A. A. Suriawinata· 2 shared

Activity by Year

2020-2021 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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4 shared papersPathology

B. Christensen

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4 papers

Recent·Most cited

Improving the Virtual Trichrome Assessment through Bridge Category Models

J. Levy, C. A. Bobak, N. Azizgolshani, X. Liu, B. Ren, M. Lisovsky, A. A. Suriawinata, B. Christensen, J. O'Malley, L. J. Vaickus

This paper assesses Virtual Trichrome technologies using Bridge Category Models to account for bridge ratings in Fibrosis staging of NASH tissue.

bioRxiv · Oct 30, 2021 · PreprintPathology

Estimating the Inter- and Intra-Rater Reliability for NASH Fibrosis Staging in the Presence of Bridge Ordinal Ratings with Hierarchical Bridge Category Models

J. Levy, C. Bobak, N. Azizgolshani, X. Liu, B. Ren, M. Lisovsky, A. Suriawinata, B. Christensen, J. O'Malley, L. Vaickus

This paper develops hierarchical Bayesian models to assess inter- and intra-rater reliability for NASH fibrosis staging, showing improved precision over ad hoc methods.

bioRxiv · Oct 27, 2021 · PreprintPathology

Bridge Category Models: Development of Bayesian Modelling Procedures to Account for Bridge Ordinal Ratings for Disease Staging

J. Levy, C. A. Bobak, N. Azizgolshani, M. J. Andersen, A. Suriawinata, X. Liu, M. Lisovsky, B. Ren, B. Christensen, L. Vaickus, J. O'Malley

The paper develops Bayesian models to handle bridge ordinal ratings in disease staging and shows they reduce bias and precision loss in models.

bioRxiv · Aug 17, 2021 · PreprintPathology

A Large-Scale Internal Validation Study of Unsupervised Virtual Trichrome Staining Technologies on Non-alcoholic Steatohepatitis Liver Biopsies

J. Levy, N. Azizgolshani, M. Andersen, A. A. Suriawinata, X. Liu, M. Lisovsky, B. Ren, C. A. Bobak, B. Christensen, L. J. Vaickus

This study validates the use of GANs for virtual trichrome staining of NASH liver biopsies, showing high correlation with real stains and clinical outcomes.

bioRxiv · Jul 3, 2020Pathology