Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning von Echle, Amelie, Grabsch, Heike Irmgard, Quirke, Philip, van den Brandt, Piet A., West, Nicholas P., Hutchins, Gordon G.A., Heij, Lara R., Tan, Xiuxiang, Richman, Susan D., Krause, Jeremias, Alwers, Elizabeth, Jenniskens, Josien, Offermans, Kelly, Gray, Richard, Brenner, Hermann, Chang-Claude, Jenny, Trautwein, Christian, Pearson, Alexander T., Boor, Peter, Luedde, Tom, Gaisa, Nadine Therese, Hoffmeister, Michael, Kather, Jakob Nikolas

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Classical mathematical models for prediction of response to chemotherapy and immunotherapy von Ghaffari Laleh, Narmin, Loeffler, Chiara Maria Lavinia, Grajek, Julia, Staňková, Kateřina, Pearson, Alexander T, Muti, Hannah Sophie, Trautwein, Christian, Enderling, Heiko, Poleszczuk, Jan, Kather, Jakob Nikolas

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Artificial intelligence-based pathology for gastrointestinal and hepatobiliary cancers von Calderaro, Julien, Kather, Jakob Nikolas

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Artificial intelligence to identify genetic alterations in conventional histopathology von Cifci, Didem, Foersch, Sebastian, Kather, Jakob Nikolas

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Deep learning in cancer pathology: a new generation of clinical biomarkers von Echle, Amelie, Rindtorff, Niklas Timon, Brinker, Titus Josef, Luedde, Tom, Pearson, Alexander Thomas, Kather, Jakob Nikolas

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Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study von Veldhuizen, Gregory Patrick, Röcken, Christoph, Behrens, Hans-Michael, Cifci, Didem, Muti, Hannah Sophie, Yoshikawa, Takaki, Arai, Tomio, Oshima, Takashi, Tan, Patrick, Ebert, Matthias P., Pearson, Alexander T., Calderaro, Julien, Grabsch, Heike I., Kather, Jakob Nikolas

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Deep learning in cancer genomics and histopathology von Unger, Michaela, Kather, Jakob Nikolas

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A systematic analysis of deep learning in genomics and histopathology for precision oncology von Unger, Michaela, Kather, Jakob Nikolas

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Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study von Kather, Jakob Nikolas, Krisam, Johannes, Charoentong, Pornpimol, Luedde, Tom, Herpel, Esther, Weis, Cleo-Aron, Gaiser, Timo, Marx, Alexander, Valous, Nektarios A, Ferber, Dyke, Jansen, Lina, Reyes-Aldasoro, Constantino Carlos, Zörnig, Inka, Jäger, Dirk, Brenner, Hermann, Chang-Claude, Jenny, Hoffmeister, Michael, Halama, Niels

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Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer von Kather, Jakob Nikolas, Pearson, Alexander T., Halama, Niels, Jäger, Dirk, Krause, Jeremias, Loosen, Sven H., Marx, Alexander, Boor, Peter, Tacke, Frank, Neumann, Ulf Peter, Grabsch, Heike I., Yoshikawa, Takaki, Brenner, Hermann, Chang-Claude, Jenny, Hoffmeister, Michael, Trautwein, Christian, Luedde, Tom

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Comparing Patient’s Confidence in Clinical Capabilities in Urology: Large Language Models Versus Urologists von Carl, Nicolas, Nguyen, Lisa, Haggenmüller, Sarah, Joachim Hetz, Martin, Theres Winterstein, Jana, Otto Hartung, Friedrich, Gruene, Britta, Nikolas Kather, Jakob, Holland-Letz, Tim, Stephan Michel, Maurice, Wessels, Frederik, Josef Brinker, Titus

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Multi-class texture analysis in colorectal cancer histology von Kather, Jakob Nikolas, Weis, Cleo-Aron, Bianconi, Francesco, Melchers, Susanne M., Schad, Lothar R., Gaiser, Timo, Marx, Alexander, Zöllner, Frank Gerrit

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Denoising diffusion probabilistic models for 3D medical image generation von Khader, Firas, Müller-Franzes, Gustav, Tayebi Arasteh, Soroosh, Han, Tianyu, Haarburger, Christoph, Schulze-Hagen, Maximilian, Schad, Philipp, Engelhardt, Sandy, Baeßler, Bettina, Foersch, Sebastian, Stegmaier, Johannes, Kuhl, Christiane, Nebelung, Sven, Kather, Jakob Nikolas, Truhn, Daniel

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Adversarial attacks and adversarial robustness in computational pathology von Ghaffari Laleh, Narmin, Truhn, Daniel, Veldhuizen, Gregory Patrick, Han, Tianyu, van Treeck, Marko, Buelow, Roman D., Langer, Rupert, Dislich, Bastian, Boor, Peter, Schulz, Volkmar, Kather, Jakob Nikolas

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Large language models streamline automated machine learning for clinical studies von Tayebi Arasteh, Soroosh, Han, Tianyu, Lotfinia, Mahshad, Kuhl, Christiane, Kather, Jakob Nikolas, Truhn, Daniel, Nebelung, Sven

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A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis von Müller-Franzes, Gustav, Niehues, Jan Moritz, Khader, Firas, Arasteh, Soroosh Tayebi, Haarburger, Christoph, Kuhl, Christiane, Wang, Tianci, Han, Tianyu, Nolte, Teresa, Nebelung, Sven, Kather, Jakob Nikolas, Truhn, Daniel

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The future landscape of large language models in medicine von Clusmann, Jan, Kolbinger, Fiona R., Muti, Hannah Sophie, Carrero, Zunamys I., Eckardt, Jan-Niklas, Laleh, Narmin Ghaffari, Löffler, Chiara Maria Lavinia, Schwarzkopf, Sophie-Caroline, Unger, Michaela, Veldhuizen, Gregory P., Wagner, Sophia J., Kather, Jakob Nikolas

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Harnessing the innate immune system and local immunological microenvironment to treat colorectal cancer von Kather, Jakob Nikolas, Halama, Niels

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Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers von Khader, Firas, Müller-Franzes, Gustav, Wang, Tianci, Han, Tianyu, Tayebi Arasteh, Soroosh, Haarburger, Christoph, Stegmaier, Johannes, Bressem, Keno, Kuhl, Christiane, Nebelung, Sven, Kather, Jakob Nikolas, Truhn, Daniel

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Pan-cancer image-based detection of clinically actionable genetic alterations von Kather, Jakob Nikolas, Heij, Lara R, Grabsch, Heike I, Loeffler, Chiara, Echle, Amelie, Muti, Hannah Sophie, Krause, Jeremias, Niehues, Jan M, Sommer, Kai A J, Bankhead, Peter, Kooreman, Loes F S, Schulte, Jefree J, Cipriani, Nicole A, Buelow, Roman D, Boor, Peter, Ortiz-Brüchle, Nadi-Na, Hanby, Andrew M, Speirs, Valerie, Kochanny, Sara, Patnaik, Akash, Srisuwananukorn, Andrew, Brenner, Hermann, Hoffmeister, Michael, van den Brandt, Piet A, Jäger, Dirk, Trautwein, Christian, Pearson, Alexander T, Luedde, Tom

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