Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer JN Kather, AT Pearson, N Halama, D Jäger, J Krause, SH Loosen, A Marx, ... Nature medicine 25 (7), 1054-1056, 2019 | 1101 | 2019 |
Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study JN Kather, J Krisam, P Charoentong, T Luedde, E Herpel, CA Weis, ... PLoS medicine 16 (1), e1002730, 2019 | 908 | 2019 |
Multi-class texture analysis in colorectal cancer histology JN Kather, CA Weis, F Bianconi, SM Melchers, LR Schad, T Gaiser, ... Scientific Reports 6, 27988, 2016 | 545 | 2016 |
Deep learning in cancer pathology: a new generation of clinical biomarkers A Echle, NT Rindtorff, TJ Brinker, T Luedde, AT Pearson, JN Kather British journal of cancer 124 (4), 686-696, 2021 | 520 | 2021 |
Pan-cancer image-based detection of clinically actionable genetic alterations JN Kather, LR Heij, HI Grabsch, C Loeffler, A Echle, HS Muti, J Krause, ... Nature cancer 1 (8), 789-799, 2020 | 507 | 2020 |
The future landscape of large language models in medicine J Clusmann, FR Kolbinger, HS Muti, ZI Carrero, JN Eckardt, NG Laleh, ... Communications medicine 3 (1), 141, 2023 | 396 | 2023 |
Clinical-grade detection of microsatellite instability in colorectal tumors by deep learning A Echle, HI Grabsch, P Quirke, PA van den Brandt, NP West, ... Gastroenterology 159 (4), 1406-1416. e11, 2020 | 279 | 2020 |
Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets MA Schulz, BTT Yeo, JT Vogelstein, J Mourao-Miranada, JN Kather, ... Nature communications 11 (1), 4238, 2020 | 277* | 2020 |
Topography of cancer-associated immune cells in human solid tumors JN Kather, M Suarez-Carmona, P Charoentong, CA Weis, D Hirsch, ... Elife 7, e36967, 2018 | 277 | 2018 |
Artificial intelligence in histopathology: enhancing cancer research and clinical oncology A Shmatko, N Ghaffari Laleh, M Gerstung, JN Kather Nature cancer 3 (9), 1026-1038, 2022 | 260 | 2022 |
The impact of site-specific digital histology signatures on deep learning model accuracy and bias FM Howard, J Dolezal, S Kochanny, J Schulte, H Chen, L Heij, D Huo, ... Nature communications 12 (1), 4423, 2021 | 244 | 2021 |
Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts S Haggenmüller, RC Maron, A Hekler, JS Utikal, C Barata, RL Barnhill, ... European Journal of Cancer 156, 202-216, 2021 | 227 | 2021 |
100,000 histological images of human colorectal cancer and healthy tissue JN Kather, N Halama, A Marx Zenodo10 5281 (9), 2018 | 208 | 2018 |
Swarm learning for decentralized artificial intelligence in cancer histopathology OL Saldanha, P Quirke, NP West, JA James, MB Loughrey, HI Grabsch, ... Nature medicine 28 (6), 1232-1239, 2022 | 158 | 2022 |
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology NG Laleh, HS Muti, CML Loeffler, A Echle, OL Saldanha, F Mahmood, ... Medical image analysis 79, 102474, 2022 | 147* | 2022 |
A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis G Müller-Franzes, JM Niehues, F Khader, ST Arasteh, C Haarburger, ... Scientific Reports 13 (1), 12098, 2023 | 144 | 2023 |
Genomics and emerging biomarkers for immunotherapy of colorectal cancer JN Kather, N Halama, D Jaeger Seminars in cancer biology 52, 189-197, 2018 | 138 | 2018 |
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction D Nam, J Chapiro, V Paradis, TP Seraphin, JN Kather Jhep Reports 4 (4), 100443, 2022 | 137 | 2022 |
Gastrointestinal cancer classification and prognostication from histology using deep learning: Systematic review S Kuntz, E Krieghoff-Henning, JN Kather, T Jutzi, J Höhn, L Kiehl, ... European Journal of Cancer 155, 200-215, 2021 | 132 | 2021 |
Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer S Foersch, C Glasner, AC Woerl, M Eckstein, DC Wagner, S Schulz, ... Nature medicine 29 (2), 430-439, 2023 | 124 | 2023 |