RESEARCHER PROFILE
Jakob Nikolas Kather
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Technische Universität Dresden
Jakob Nikolas Kather works in AI in cancer detection, Artificial Intelligence in Healthcare and Education, Radiomics and Machine Learning in Medical Imaging, Machine Learning in Healthcare, Cancer Immunotherapy and Biomarkers. Recorded institutional associations include University of Leeds, German Cancer Research Center, Heidelberg University.
644Publications
22,257Citations
77H-index
Inclusion identifies researchers whose recorded research contributions may inform their university’s understanding of its research community. It does not rank individual research quality or establish current employment.
Selected research works
Up to 100 highly cited works; DOI links open the original research. Counts reflect the collected record, not real-time citation totals.
Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer
2019 · 1,442 citationsPredicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study
2019 · 1,075 citationsThe future landscape of large language models in medicine
2023 · 1,026 citationsPan-cancer image-based detection of clinically actionable genetic alterations
2020 · 662 citationsDeep learning in cancer pathology: a new generation of clinical biomarkers
2020 · 660 citationsMulti-class texture analysis in colorectal cancer histology
2016 · 574 citationsArtificial intelligence in histopathology: enhancing cancer research and clinical oncology
2022 · 439 citationsClinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning
2020 · 372 citationsCurrent applications and challenges in large language models for patient care: a systematic review
2025 · 343 citationsDenoising diffusion probabilistic models for 3D medical image generation
2023 · 338 citationsArtificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review
2023 · 337 citationsThe impact of site-specific digital histology signatures on deep learning model accuracy and bias
2021 · 319 citationsDifferent scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets
2020 · 311 citationsTopography of cancer-associated immune cells in human solid tumors
2018 · 280 citationsTransformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study
2023 · 273 citationsSkin cancer classification via convolutional neural networks: systematic review of studies involving human experts
2021 · 267 citationsMultistain deep learning for prediction of prognosis and therapy response in colorectal cancer
2023 · 250 citationsESMO Guidance for Reporting Oncology real-World evidence (GROW)
2023 · 234 citationsArtificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
2022 · 226 citationsSwarm learning for decentralized artificial intelligence in cancer histopathology
2022 · 225 citationsA multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis
2023 · 214 citationsA guide to artificial intelligence for cancer researchers
2024 · 211 citationsGastrointestinal cancer classification and prognostication from histology using deep learning: Systematic review
2021 · 191 citations100,000 Histological Images Of Human Colorectal Cancer And Healthy Tissue
2018 · 180 citationsBenchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology
2022 · 179 citations