| 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 | 421 | 2020 |
| 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 | 397 | 2021 |
| 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 | 236 | 2020 |
| 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 | 96 | 2022 |
| Artificial intelligence for detection of microsatellite instability in colorectal cancer—a multicentric analysis of a pre-screening tool for clinical application A Echle, NG Laleh, P Quirke, HI Grabsch, HS Muti, OL Saldanha, ... ESMO open 7 (2), 100400, 2022 | 64 | 2022 |
| Weakly supervised annotation‐free cancer detection and prediction of genotype in routine histopathology PL Schrammen, N Ghaffari Laleh, A Echle, D Truhn, V Schulz, TJ Brinker, ... The Journal of pathology 256 (1), 50-60, 2022 | 62 | 2022 |
| Deep learning detects genetic alterations in cancer histology generated by adversarial networks J Krause, HI Grabsch, M Kloor, M Jendrusch, A Echle, RD Buelow, P Boor, ... The Journal of pathology 254 (1), 70-79, 2021 | 53 | 2021 |
| Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer S Brockmoeller, A Echle, N Ghaffari Laleh, S Eiholm, ML Malmstrøm, ... The Journal of pathology 256 (3), 269-281, 2022 | 43 | 2022 |
| Deep learning for the detection of microsatellite instability from histology images in colorectal cancer: a systematic literature review A Echle, NG Laleh, PL Schrammen, NP West, C Trautwein, TJ Brinker, ... ImmunoInformatics 3, 100008, 2021 | 29 | 2021 |
| The future of artificial intelligence in digital pathology–results of a survey across stakeholder groups CN Heinz, A Echle, S Foersch, A Bychkov, JN Kather Histopathology 80 (7), 1121-1127, 2022 | 26 | 2022 |
| The Aachen protocol for deep learning histopathology: a hands-on guide for data preprocessing HS Muti, C Loeffler, A Echle, LR Heij, RD Buelow, J Krause, L Broderius, ... Zenodo, 2020 | 17 | 2020 |
| Predicting mutational status of driver and suppressor genes directly from histopathology with deep learning: a systematic study across 23 solid tumor types CML Loeffler, NT Gaisa, HS Muti, M van Treeck, A Echle, N Ghaffari Laleh, ... Frontiers in Genetics 12, 806386, 2022 | 14 | 2022 |
| Benchmarking artificial intelligence methods for end-to-end computational pathology NG Laleh, HS Muti, CM Lavinia Loeffler, A Echle, OL Saldanha, ... bioRxiv, 2021.08. 09.455633, 2021 | 10 | 2021 |
| DeepMed: a unified, modular pipeline for end-to-end deep learning in computational pathology M van Treeck, D Cifci, NG Laleh, OL Saldanha, CML Loeffler, KJ Hewitt, ... BioRxiv, 2021.12. 19.473344, 2021 | 9 | 2021 |
| Validation of the prognostic value of CD3 and CD8 cell densities analogous to the Immunoscore® by stage and location of colorectal cancer: an independent patient cohort study E Alwers, JN Kather, M Kloor, A Brobeil, KE Tagscherer, W Roth, A Echle, ... The Journal of Pathology: Clinical Research 9 (2), 129-136, 2023 | 6 | 2023 |
| Deep Learning for interpretable end-to-end survival (E-ESurv) prediction in gastrointestinal cancer histopathology NG Laleh, A Echle, HS Muti, KJ Hewitt, S Volkmar, JN Kather MICCAI Workshop on Computational Pathology, 81-93, 2021 | 3 | 2021 |
| Author Correction: 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 (11), 1129-1129, 2020 | 3 | 2020 |
| Deep learning for interpretable end-to-end survival prediction in gastrointestinal cancer histopathology NG Laleh, A Echle, HS Muti, KJ Hewitt, V Schulz, JN Kather COMPAY 2021: The third MICCAI workshop on Computational Pathology, 2021 | 2 | 2021 |
| Erratum to'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology'Medical Image Analysis, Volume 79, July 2022, 102474. HS Muti, CML Loeffler, A Echle, OL Saldanha, F Mahmood, MY Lu, ... Medical Image Analysis 82, 102622-102622, 2022 | | 2022 |
| Cross-Cancer Deployment of a Deep Learning-Based Classifier for Microsatellite Instability in Gastric, Colorectal and Endometrial Cancer HS Muti, A Echle, C Loeffler, M Kohlruss, G Keller, P Quirke, N West, ... JOURNAL OF PATHOLOGY 255, S15-S15, 2021 | | 2021 |
