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BMC Medical Informatics and Decision Making|July 3, 2026
Established machine learning matches tabular foundation models in clinical predictionsLawrence A Shaktah, Marco Gustav, Tim Lenz, et al.
The Lancet. Digital Health|November 15, 2025
Application of artificial intelligence and digital tools in cancer pathologyLawrence A Shaktah, Zunamys I Carrero, Katherine Jane Hewitt, et al.
NPJ Precision Oncology|July 3, 2026
Mutation enrichment in targeted panels flags immunotherapy-responsive POLE-driven hypermutated microsatellite-stable colorectal cancersNic Gabriel Reitsam, Kathrin Anna Schneider, Bianca Grosser, et al.
Digestion|March 6, 2025
Weakly Supervised Deep Learning Can Analyze Focal Liver Lesions in Contrast-Enhanced UltrasoundAdil Oezsoy, James Alexander Brooks, Marko van Treeck, et al.
NPJ Precision Oncology|May 23, 2024
Deep learning for dual detection of microsatellite instability and POLE mutations in colorectal cancer histopathologyMarco Gustav, Nic Gabriel Reitsam, Zunamys I Carrero, et al.
Medrxiv : the Preprint Server for Health Sciences|March 22, 2023
Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation studyChiara Maria Lavinia Loeffler, Omar S M El Nahhas, Hannah Sophie Muti, et al.
BMC Biology|October 8, 2024
Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor typesChiara Maria Lavinia Loeffler, Omar S M El Nahhas, Hannah Sophie Muti, et al.
Medrxiv : the Preprint Server for Health Sciences|February 20, 2025
Assessing Genotype-Phenotype Correlations with Deep Learning in Colorectal Cancer: A Multi-Centric StudyMarco Gustav, Marko van Treeck, Nic G Reitsam, et al.
The Lancet. Digital Health|August 19, 2025
Assessing genotype-phenotype correlations in colorectal cancer with deep learning: a multicentre cohort studyMarco Gustav, Marko van Treeck, Nic G Reitsam, et al.
The Journal of Pathology|February 20, 2026
Deep learning-based H&E-derived risk scores in colorectal cancer: associations with tumour morphology, biology, and predicted drug responseNic G Reitsam, Xiaofeng Jiang, Junhao Liang, et al.
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