| 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 | 437 | 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 | 167 | 2023 |
| 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 | 102 | 2022 |
| Artificial intelligence–based detection of FGFR3 mutational status directly from routine histology in bladder cancer: a possible preselection for molecular testing? CML Loeffler, NO Bruechle, M Jung, L Seillier, M Rose, NG Laleh, ... European urology focus 8 (2), 472-479, 2022 | 58 | 2022 |
| Classical mathematical models for prediction of response to chemotherapy and immunotherapy N Ghaffari Laleh, CML Loeffler, J Grajek, K Staňková, AT Pearson, ... PLoS computational biology 18 (2), e1009822, 2022 | 43 | 2022 |
| Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology OL Saldanha, CML Loeffler, JM Niehues, M van Treeck, TP Seraphin, ... NPJ Precision Oncology 7 (1), 35, 2023 | 40 | 2023 |
| An overview and a roadmap for artificial intelligence in hematology and oncology W Rösler, M Altenbuchinger, B Baeßler, T Beissbarth, G Beutel, R Bock, ... Journal of cancer research and clinical oncology 149 (10), 7997-8006, 2023 | 29 | 2023 |
| Deep learning detects virus presence in cancer histology JN Kather, J Schulte, HI Grabsch, C Loeffler, H Muti, J Dolezal, ... BioRxiv, 690206, 2019 | 21 | 2019 |
| 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 | 16 | 2022 |
| Regression-based Deep-Learning predicts molecular biomarkers from pathology slides OSM El Nahhas, CML Loeffler, ZI Carrero, M van Treeck, FR Kolbinger, ... Nature communications 15 (1), 1253, 2024 | 11 | 2024 |
| 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 |
| Extracting structured information from unstructured histopathology reports using generative pre‐trained transformer 4 (GPT‐4) D Truhn, CML Loeffler, G Müller‐Franzes, S Nebelung, KJ Hewitt, ... The Journal of Pathology 262 (3), 310-319, 2024 | 8 | 2024 |
| Characterisation of tumour-immune phenotypes and PD-L1 positivity in squamous bladder cancer M Jung, M Rose, R Knuechel, C Loeffler, H Muti, JN Kather, NT Gaisa, ... BMC cancer 23 (1), 113, 2023 | 7 | 2023 |
| The Aachen protocol for deep learning histopathology: a hands-on guide for data preprocessing. 2020 HS Muti, C Loeffler, A Echle, LR Heij, RD Buelow, J Krause Zenodo, 0 | 5 | |
| Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study HS Muti, C Röcken, HM Behrens, CML Löffler, NG Reitsam, B Grosser, ... European Journal of Cancer 194, 113335, 2023 | 4 | 2023 |
| Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and … CML Loeffler, OSM El Nahhas, HS Muti, T Seibel, D Cifci, M van Treeck, ... medRxiv, 2023 | 4 | 2023 |
| Prediction models for hormone receptor status in female breast cancer do not extend to males: further evidence of sex-based disparity in breast cancer S Chatterji, JM Niehues, M van Treeck, CML Loeffler, OL Saldanha, ... NPJ Breast Cancer 9 (1), 91, 2023 | 2 | 2023 |
| Direct image to subtype prediction for brain tumors using deep learning KJ Hewitt, CML Löffler, HS Muti, AS Berghoff, C Eisenlöffel, M van Treeck, ... Neuro-oncology advances 5 (1), vdad139, 2023 | 2 | 2023 |
