Author

M. Veta

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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Bioengineering· 1 Immunology· 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 Research Focus:benchmarking· 1 Approach:statistical model· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

A. D. Harris· 1 shared A. Qayyum· 1 shared C. A. Rubadue· 1 shared C. Rodero· 1 shared D. I. Lin· 1 shared D. M. J. Van de Sande· 1 shared G. Dias· 1 shared G. S. Drenthen· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioengineering

A. D. Harris

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Author profile →

3 papers

Recent·Most cited

Advancing GABA-edited MRS Research through a Reconstruction Challenge

R. P. Berto, H. Bugler, G. Dias, M. Oliveira, L. Ueda, S. Dertkigil, P. D. P. Costa, L. Rittner, J. P. Merkofer, D. M. J. Van de Sande, S. Amirrajab, G. S. Drenthen, M. Veta, J. F. A. Jansen, M. Breeuwer, , A. D. Harris

This paper presents a benchmark challenge to compare machine learning models for GABA-edited MRS reconstruction using reduced transients, finding that deep learning models achieve comparable metrics to conventional methods.

bioRxiv · Sep 21, 2023Bioengineering

Differentiation of leukocytes in bronchoalveolar lavage fluid samples using higher harmonic generation microscopy and deep learning

L. M. G. van Huizen, M. Blokker, Y. Rip, M. Veta, K. A. Mooij - Kalverda, P. I. Bonta, J. W. W. Duitman, M. L. Groot

This paper uses higher harmonic generation microscopy and deep learning to differentiate leukocytes in BALF samples, achieving reasonable accuracy in estimating leukocyte ratios.

bioRxiv · Dec 12, 2022 · PreprintImmunology

Automated Clear Cell Renal Carcinoma Grade Classification with Prognostic Significance

K. Tian, C. A. Rubadue, D. I. Lin, M. Veta, M. E. Pyle, H. Irshad, Y. J. Heng

The paper develops an automated 2-tiered Fuhrman grading system for ccRCC using WSI and clinical data, showing prognostic significance in an extended test set.

bioRxiv · Jun 6, 2019Pathology