Jakob Nikolas Kather
Orcid: 0000-0002-3730-5348
According to our database1,
Jakob Nikolas Kather
authored at least 47 papers
between 2017 and 2024.
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Bibliography
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
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
Large Language Models-Enabled Digital Twins for Precision Medicine in Rare Gynecological Tumors.
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
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