Jacob Gildenblat
About me Papers Patents

Papers

  • Preserving clusters and correlations: a dimensionality reduction method for exceptionally high global structure preservation 2025, arxiv preprint, Jacob Gildenblat, Jens Pahnke

  • Segmentation by Factorization: Unsupervised Semantic Segmentation for Pathology by Factorizing Foundation Model Features 2025, arxiv preprint, Jacob Gildenblat, Ofir Hadar

  • Multi-modal machine learning approaches for predicting cancer type and Gleason grade leveraging public TCGA data 2024 American Association of Cancer Research

  • Deep Cellular Embeddings: An Explainable Plug and Play Improvement for Feature Representation in Histopathology 2023 MICCAI, Jacob Gildenblat, Anil Yüce, Samaneh Abbasi-Sureshjani, Konstanty Korski

  • Artificial intelligence-assisted interpretation of colonic biopsies from patients with inflammatory bowel disease 2024, European Congress of Pathology | Adam P. Levine, Ofir Hadar, Hannah Lowes, Jacob Gildenblat, Talisa Mistry, Dahmane Oukrif, Chen Sagiv, Manuel Rodriguez-Justo

  • A decision support system for the detection of cutaneous fungal infections using artificial intelligence 2024, Pathology - Research and Practice | Naama Rappoport, Ofir Hadar, Gil Goldinger, Assaf Debby, Yosef Molchanov, Yoash Barak, Jacob Gildenblat, Chen Sagiv, Aviv Barzilai

  • Identification of MYC -Driven High-Grade B-Cell Lymphoma Using Deep Learning-Based Whole Slide Image Analysis 2023 November Blood

  • Predicting Cell Of Origin from digitized images of hematoxylin and eosin-stained slides of diffuse large b-cell lymphomas using a cell-based deep-learning model 2023, 17th International Conference on Malignant Lymphoma

  • HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin–Eosin Whole-Slide Imaging 2022

  • Deep learning for sensitive detection of Helicobacter Pylori in gastric biopsies 2020 Sebastian Klein, Jacob Gildenblat, Michaele Angelika Ihle, Sabine Merkelbach-Bruse, Ka-Won Noh, Martin Peifer, Alexander Quaas & Reinhard Büttner

  • Certainty Pooling for Multiple Instance Learning 2020 Jacob Gildenblat, Ido Ben-Shaul, Zvi Lapp, Eldad Klaiman

  • Self-Supervised Similarity Learning for Digital Pathology 2019 Jacob Gildenblat, Eldad Klaiman

  • Prediction of biomarker status, diagnosis and outcome from histology slides using deep learning-based hypothesis free feature extraction 2018 Eldad Klaiman, Jacob Gildenblat, Ido Ben-Shaul, Astrid Heller, Konstanty Korski, Astrid Christina Kiermaier, Fabien Gaire

  • Virtualization of tissue staining in digital pathology using an unsupervised deep learning approach 2018 Amal Lahiani, Jacob Gildenblat, Irina Klaman, Shadi Albarqouni, Nassir Navab, Eldad Klaiman

  • Generalizing multistain immunohistochemistry tissue segmentation using one-shot color deconvolution deep neural networks 2018 Amal Lahiani, Jacob Gildenblat, Irina Klaman, Nassir Navab, Eldad Klaiman