Jakub Kaczmarzyk

Stony Brook University — United States

Medicine · Health Sciences

12h-index883citations54works9.92yr avg
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Research Topics

Radiomics and Machine Learning in Medical Imaging(13), Cell Image Analysis Techniques(13), Functional Brain Connectivity Studies(12), AI in cancer detection(11), Electron and X-Ray Spectroscopy Techniques(6)

Publications54 total

Towards interpretable prediction of recurrence risk in breast cancer using pathology foundation models
arXiv (Cornell University)·2025Open Access
Abstract 5315: Mapping tumor infiltrating lymphocytes in whole prostatectomy specimens to visualize and quantify the immune microenvironment of prostate cancer
Cancer Research·2025
Reusable specimen-level inference in computational pathology
PubMed·2025Open Access
Explainable AI for computational pathology identifies model limitations and tissue biomarkers
PubMed·2024· 1 citedOpen Access
Abstract B082: Early risk stratification of ER+/HER2– breast cancer patients using digital pathology and multi-task, weakly-supervised deep learning
Cancer Research·2024
Open and reusable deep learning for pathology with WSInfer and QuPath
npj Precision Oncology·2024· 22 citedOpen Access
Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging
Nature Methods·2024· 53 citedOpen Access
An Intelligent Search & Retrieval System (IRIS) and Clinical and Research Repository for Decision Support Based on Machine Learning and Joint Kernel-based Supervised Hashing
Cancer Informatics·2024· 3 citedOpen Access
Open and reusable deep learning for pathology with WSInfer and QuPath
arXiv (Cornell University)·2023· 1 citedOpen Access
ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification
Computer Methods and Programs in Biomedicine·2023· 15 citedOpen Access
AI and Pathology: Steering Treatment and Predicting Outcomes
WORLD SCIENTIFIC eBooks·2023· 1 cited
Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging
2023· 5 citedOpen Access
Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging
2022· 8 citedOpen Access
Deep neural networks allow expert-level brain meningioma segmentation and present potential for improvement of clinical practice
Scientific Reports·2022· 24 citedOpen Access
AI and Pathology: Steering Treatment and Predicting Outcomes
arXiv (Cornell University)·2022Open Access
Evaluating histopathology transfer learning with ChampKit
arXiv (Cornell University)·2022Open Access
Dataset for tumor infiltrating lymphocyte classification (304,097 image patches from TCGA)
Zenodo (CERN European Organization for Nuclear Research)·2022· 2 citedOpen Access
Dataset for tumor infiltrating lymphocyte classification (304,097 image patches from TCGA)
2022· 1 citedOpen Access
A Novel Framework for Characterization of Tumor-Immune Spatial Relationships in Tumor Microenvironment
arXiv (Cornell University)·2022Open Access
Classification of glioblastoma versus primary central nervous system lymphoma using convolutional neural networks
Scientific Reports·2021· 47 citedOpen Access
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Frequent Co-authors

Satrajit Ghosh(28), Mathias Goncalves(18), Yaroslav O. Halchenko(16), Christopher J. Markiewicz(14), Michael Hanke(13), Christian Haselgrove(12), Jean‐Baptiste Poline(12), Tahsin Kurç(12), Joel Saltz(12), Matthew Brett(11), Marc-Alexandre Côté(10), Ben Cipollini(10), Paul J. McCarthy(10), Christopher Cheng(10), Michiel Cottaar(10), Demián Wassermann(10), Stephan Gerhard(10), Gregory R. Lee(10), Erik K. Kastman(10), Ariel Rokem(10)