A deep learning framework for efficient pathology image analysis

Authors: Neidlinger, Peter, Lenz, Tim, Foersch, Sebastian, Loeffler, Chiara M. L., Clusmann, Jan, Gustav, Marco, Shaktah, Lawrence A., Langer, Rupert, Dislich, Bastian, Boardman, Lisa A., French, Amy J., Goode, Ellen L., Gsur, Andrea, Brezina, Stefanie, Gunter, Marc J., Steinfelder, Robert, Behrens, Hans-Michael, Röcken, Christoph, Harrison, Tabitha, Peters, Ulrike, Phipps, Amanda I., Curigliano, Giuseppe, Fusco, Nicola, Marra, Antonio, Hoffmeister, Michael, Brenner, Hermann, Kather, Jakob Nikolas

Subject Terms: Computer Science - Computer Vision and Pattern Recognition

Access URL: http://arxiv.org/abs/2502.13027

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides

Authors: Nahhas, Omar S. M. El, Loeffler, Chiara M. L., Carrero, Zunamys I., van Treeck, Marko, Kolbinger, Fiona R., Hewitt, Katherine J., Muti, Hannah S., Graziani, Mara, Zeng, Qinghe, Calderaro, Julien, Ortiz-Brüchle, Nadina, Yuan, Tanwei, Hoffmeister, Michael, Brenner, Hermann, Brobeil, Alexander, Reis-Filho, Jorge S., Kather, Jakob Nikolas

Subject Terms: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence

Access URL: http://arxiv.org/abs/2304.05153

Multimodal histopathologic models stratify hormone receptor-positive early breast cancer.

Authors: Boehm, Kevin M., El Nahhas, Omar S. M., Marra, Antonio, Waters, Michele, Jee, Justin, Braunstein, Lior, Schultz, Nikolaus, Selenica, Pier, Wen, Hannah Y., Weigelt, Britta, Paul, Evan D., Cekan, Pavol, Erber, Ramona, Loeffler, Chiara M. L., Guerini-Rocco, Elena, Fusco, Nicola, Frascarelli, Chiara, Mane, Eltjona, Munzone, Elisabetta, Dellapasqua, Silvia

Source: Nature Communications; 3/2/2025, Vol. 16 Issue 1, p1-14, 14p

Subject Terms: MACHINE learning, BREAST cancer, PROGNOSIS, CLINICAL pathology, METASTASIS

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

Authors: El Nahhas, Omar S. M., Loeffler, Chiara M. L., Carrero, Zunamys I., van Treeck, Marko, Kolbinger, Fiona R., Hewitt, Katherine J., Muti, Hannah S., Graziani, Mara, Zeng, Qinghe, Calderaro, Julien, Ortiz-Brüchle, Nadina, Yuan, Tanwei, Hoffmeister, Michael, Brenner, Hermann, Brobeil, Alexander, Reis-Filho, Jorge S., Kather, Jakob Nikolas

Source: Nature Communications; 9/16/2024, Vol. 15 Issue 1, p1-13, 13p

Subject Terms: TUMOR markers, HOMOLOGOUS recombination, DEEP learning, BIOMARKERS, COLORECTAL cancer

Automated curation of large‐scale cancer histopathology image datasets using deep learning.

Authors: Hilgers, Lars, Ghaffari Laleh, Narmin, West, Nicholas P, Westwood, Alice, Hewitt, Katherine J, Quirke, Philip, Grabsch, Heike I, Carrero, Zunamys I, Matthaei, Emylou, Loeffler, Chiara M L, Brinker, Titus J, Yuan, Tanwei, Brenner, Hermann, Brobeil, Alexander, Hoffmeister, Michael, Kather, Jakob Nikolas

Source: Histopathology; Jun2024, Vol. 84 Issue 7, p1139-1153, 15p

Subject Terms: DEEP learning, ARTIFICIAL neural networks, CONVOLUTIONAL neural networks, HISTOPATHOLOGY, ARTIFICIAL intelligence, COLORECTAL cancer

Geographic Terms: GERMANY, UNITED Kingdom

Deep learning for dual detection of microsatellite instability and POLE mutations in colorectal cancer histopathology.

Authors: Gustav, Marco, Reitsam, Nic Gabriel, Carrero, Zunamys I., Loeffler, Chiara M. L., van Treeck, Marko, Yuan, Tanwei, West, Nicholas P., Quirke, Philip, Brinker, Titus J., Brenner, Hermann, Favre, Loëtitia, Märkl, Bruno, Stenzinger, Albrecht, Brobeil, Alexander, Hoffmeister, Michael, Calderaro, Julien, Pujals, Anaïs, Kather, Jakob Nikolas

Source: NPJ Precision Oncology; 5/23/2024, Vol. 8 Issue 1, p1-11, 11p

Subject Terms: DEEP learning, DNA mismatch repair, COLORECTAL cancer, MICROSATELLITE repeats, DNA polymerases, COLON tumors, HEREDITARY nonpolyposis colorectal cancer

An overview and a roadmap for artificial intelligence in hematology and oncology.

Authors: Rösler, Wiebke, Altenbuchinger, Michael, Baeßler, Bettina, Beissbarth, Tim, Beutel, Gernot, Bock, Robert, von Bubnoff, Nikolas, Eckardt, Jan-Niklas, Foersch, Sebastian, Loeffler, Chiara M. L., Middeke, Jan Moritz, Mueller, Martha-Lena, Oellerich, Thomas, Risse, Benjamin, Scherag, André, Schliemann, Christoph, Scholz, Markus, Spang, Rainer, Thielscher, Christian, Tsoukakis, Ioannis

Source: Journal of Cancer Research & Clinical Oncology; Aug2023, Vol. 149 Issue 10, p7997-8006, 10p

Subject Terms: ARTIFICIAL intelligence, MEDICAL personnel, ONCOLOGY, HEMATOLOGY, LANGUAGE models

Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology.

Authors: Saldanha, Oliver Lester, Loeffler, Chiara M. L., Niehues, Jan Moritz, van Treeck, Marko, Seraphin, Tobias P., Hewitt, Katherine Jane, Cifci, Didem, Veldhuizen, Gregory Patrick, Ramesh, Siddhi, Pearson, Alexander T., Kather, Jakob Nikolas

Source: NPJ Precision Oncology; 3/28/2023, Vol. 7 Issue 1, p1-5, 5p

Subject Terms: DEEP learning, HISTOPATHOLOGY, FEATURE extraction, FORECASTING, MOLECULAR pathology

Author Correction: Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

Authors: El Nahhas, Omar S. M., Loeffler, Chiara M. L., Carrero, Zunamys I., van Treeck, Marko, Kolbinger, Fiona R., Hewitt, Katherine J., Muti, Hannah S., Graziani, Mara, Zeng, Qinghe, Calderaro, Julien, Ortiz-Brüchle, Nadina, Yuan, Tanwei, Hoffmeister, Michael, Brenner, Hermann, Brobeil, Alexander, Reis-Filho, Jorge S., Kather, Jakob Nikolas

Source: Nature Communications; 2/29/2024, Vol. 15 Issue 1, p1-1, 1p

Subject Terms: MOLECULAR pathology, BIOMARKERS, PATHOLOGY, APPLIED sciences