Jakob Nikolas Kather
Orcid: 0000-0002-3730-5348
According to our database1,
Jakob Nikolas Kather
authored at least 60 papers
between 2017 and 2025.
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Bibliography
2025
J. Heal. Informatics Res., September, 2025
Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections.
CoRR, April, 2025
CoRR, February, 2025
How machine learning on real world clinical data improves adverse event recording for endoscopy.
npj Digit. Medicine, 2025
npj Digit. Medicine, 2025
Large language models-enabled digital twins for precision medicine in rare gynecological tumors.
npj Digit. Medicine, 2025
Benchmarking vision-language models for diagnostics in emergency and critical care settings.
npj Digit. Medicine, 2025
Diagnosis with Nanoscale Protein Distributions: Single-Molecule Fluorescence Localization Microscopy and Attention-Based Learning.
Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
2024
Encrypted federated learning for secure decentralized collaboration in cancer image analysis.
Medical Image Anal., February, 2024
Privacy-preserving large language models for structured medical information retrieval.
npj Digit. Medicine, 2024
npj Digit. Medicine, 2024
npj Digit. Medicine, 2024
npj Digit. Medicine, 2024
Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2.
CoRR, 2024
Pathologist-like explainable AI for interpretable Gleason grading in prostate cancer.
CoRR, 2024
Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study.
CoRR, 2024
Benchmarking foundation models as feature extractors for weakly-supervised computational pathology.
CoRR, 2024
RadioRAG: Factual Large Language Models for Enhanced Diagnostics in Radiology Using Dynamic Retrieval Augmented Generation.
CoRR, 2024
Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization.
CoRR, 2024
CoRR, 2024
In-context learning enables multimodal large language models to classify cancer pathology images.
CoRR, 2024
Reducing self-supervised learning complexity improves weakly-supervised classification performance in computational pathology.
CoRR, 2024
Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance.
Comput. Biol. Medicine, 2024
Joint Multi-task Learning Improves Weakly-Supervised Biomarker Prediction in Computational Pathology.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification.
Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024
2023
Machine learning in the identification of prognostic DNA methylation biomarkers among patients with cancer: A systematic review of epigenome-wide studies.
Artif. Intell. Medicine, September, 2023
From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology.
CoRR, 2023
A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology.
CoRR, 2023
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining.
CoRR, 2023
CoRR, 2023
Empowering Clinicians and Democratizing Data Science: Large Language Models Automate Machine Learning for Clinical Studies.
CoRR, 2023
Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images.
CoRR, 2023
Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study.
CoRR, 2023
Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers - A multi-institutional evaluation.
CoRR, 2023
CoRR, 2023
Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study.
CoRR, 2023
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
2022
Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation.
Nat. Mac. Intell., November, 2022
Classical mathematical models for prediction of response to chemotherapy and immunotherapy.
PLoS Comput. Biol., 2022
Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474.
Medical Image Anal., 2022
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.
Medical Image Anal., 2022
Medical Diagnosis with Large Scale Multimodal Transformers: Leveraging Diverse Data for More Accurate Diagnosis.
CoRR, 2022
Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels.
CoRR, 2022
Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation.
CoRR, 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2021
Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning.
CoRR, 2021
Deep Learning for interpretable end-to-end survival (E-ESurv) prediction in gastrointestinal cancer histopathology.
Proceedings of the MICCAI Workshop on Computational Pathology, 2021
2019
Evaluation of Colour Pre-processing on Patch-Based Classification of H&E-Stained Images.
Proceedings of the Digital Pathology - 15th European Congress, 2019
2017
Dimensionality Reduction Strategies for CNN-Based Classification of Histopathological Images.
Proceedings of the Intelligent Interactive Multimedia Systems and Services 2017, 2017