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Article
Open AccessAn overview and a roadmap for artificial intelligence in hematology and oncology
Artificial intelligence (AI) is influencing our society on many levels and has broad implications for the future practice of hematology and oncology. However, for many medical professionals and researchers, it...
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Article
Open AccessDenoising diffusion probabilistic models for 3D medical image generation
Recent advances in computer vision have shown promising results in image generation. Diffusion probabilistic models have generated realistic images from textual input, as demonstrated by DALL-E 2, Imagen, and ...
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Article
Open AccessDirect prediction of genetic aberrations from pathology images in gastric cancer with swarm learning
Computational pathology uses deep learning (DL) to extract biomarkers from routine pathology slides. Large multicentric datasets improve performance, but such datasets are scarce for gastric cancer. This limit...
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Article
Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer
Although it has long been known that the immune cell composition has a strong prognostic and predictive value in colorectal cancer (CRC), scoring systems such as the immunoscore (IS) or quantification of intra...
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Article
Open AccesspT3 colorectal cancer revisited: a multicentric study on the histological depth of invasion in more than 1000 pT3 carcinomas—proposal for a new pT3a/pT3b subclassification
Pathological TNM staging (pTNM) is the strongest prognosticator in colorectal carcinoma (CRC) and the foundation of its post-operative clinical management. Tumours that invade pericolic/perirectal adipose tiss...
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Article
Open AccessMedical domain knowledge in domain-agnostic generative AI
The text-guided diffusion model GLIDE (Guided Language to Image Diffusion for Generation and Editing) is the state of the art in text-to-image generative artificial intelligence (AI). GLIDE has rich representa...
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Article
Open AccessSwarm learning for decentralized artificial intelligence in cancer histopathology
Artificial intelligence (AI) can predict the presence of molecular alterations directly from routine histopathology slides. However, training robust AI systems requires large datasets for which data collection...
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Article
Open AccessLoss of CDX2 in colorectal cancer is associated with histopathologic subtypes and microsatellite instability but is prognostically inferior to hematoxylin–eosin-based morphologic parameters from the WHO classification
Immunohistochemical loss of CDX2 has been proposed as a biomarker of dismal survival in colorectal carcinoma (CRC), especially in UICC Stage II/III. However, it remains unclear, how CDX2 expression is related ...
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Article
Open AccessComparative analysis of nuclear and mitochondrial DNA from tissue and liquid biopsies of colorectal cancer patients
The current standard for molecular profiling of colorectal cancer (CRC) is using resected or biopsied tissue specimens. However, they are limited regarding sampling frequency, representation of tumor heterogen...
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Article
Open AccessChronic intestinal inflammation drives colorectal tumor formation triggered by dietary heme iron in vivo
The consumption of red meat is associated with an increased risk for colorectal cancer (CRC). Multiple lines of evidence suggest that heme iron as abundant constituent of red meat is responsible for its carcin...
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Article
Colitis-associated neoplasia: molecular basis and clinical translation
Crohn’s disease and ulcerative colitis are both associated with an increased risk of inflammation-associated colorectal carcinoma. Colitis-associated cancer (CAC) is one of the most important causes for morbi...
