55 citations · 158 across the 26 of their papers we have counts for
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q-bio.TO2025
Towards interpretable prediction of recurrence risk in breast cancer using pathology foundation models
Jakub R. Kaczmarzyk, Sarah C. Van Alsten, Alyssa J. Cozzo +5
Transcriptomic assays such as the PAM50-based ROR-P score guide recurrence risk stratification in non-metastatic, ER-positive, HER2-negative breast cancer but are not universally a…
q-bio.TO2023★ 25 cited
Open and reusable deep learning for pathology with WSInfer and QuPath
Jakub R. Kaczmarzyk, Alan O'Callaghan, Fiona Inglis +5
The field of digital pathology has seen a proliferation of deep learning models in recent years. Despite substantial progress, it remains rare for other researchers and pathologist…