Author

Salma Kazemi Rashed

Lund UniversityORCID 0000-0002-2345-8167Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:imaging· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Sonja AitsiD· 2 shared August Lidfeldt· 1 shared Darcy Elizabeth WagneriD· 1 shared Iran A. N. SilvaiD· 1 shared John StegmayriD· 1 shared Ludwig Hedlund· 1 shared Mikael NilssoniD· 1 shared Nika GvazavaiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 29 mutual co-author links

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2 shared papersPathology

Sonja AitsORCID

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2 papers

Recent·Most cited

Improving Data Quality, Model Transparency and Performance in Lung Histopathology with Explainable AI

Salma Kazemi Rashed, Mikael Nilsson, Sonja Aits

This paper applies explainable AI techniques to improve transparency, data quality, and performance in lung histopathology image classification.

bioRxiv · Sep 21, 2026 · PreprintPathology

Deep learning for rapid and reproducible histology scoring of lung injury in a porcine model

Iran A. N. Silva, Salma Kazemi Rashed, Ludwig Hedlund, August Lidfeldt, Nika Gvazava, John Stegmayr, V. R. Skoryk, Sonja Aits, Darcy Elizabeth Wagner

This study evaluates the reproducibility of human histology scoring for ARDS in a porcine model and demonstrates that CNNs can automate the process with acceptable performance.

bioRxiv · May 12, 2023 · PreprintBioinformatics