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VOLTA: an enVironment-aware cOntrastive ceLl represenTation leArning for histopathology
In clinical oncology, many diagnostic tasks rely on the identification of cells in histopathology images. While supervised machine learning...
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Generalization of vision pre-trained models for histopathology
Out-of-distribution (OOD) generalization, especially for medical setups, is a key challenge in modern machine learning which has only recently...
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AI-based histopathology image analysis reveals a distinct subset of endometrial cancers
Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No...
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Validation of CT-based ventilation and perfusion biomarkers with histopathology confirms radiation-induced pulmonary changes in a porcine model
Imaging biomarkers can assess disease progression or prognoses and are valuable tools to help guide interventions. Particularly in lung imaging,...
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Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology
A model’s ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational...
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Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning
Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy. Spatial transcriptomics technologies may...
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Chronic dehydration induces injury pathways in rats, but does not mimic histopathology of chronic interstitial nephritis in agricultural communities
CINAC-patients present renal proximal tubular cell lysosomal lesions which are also observed in patients experiencing calcineurin inhibitor (CNI)...
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Implementation of an interactive virtual microscope laboratory system in teaching oral histopathology
Laboratory course acts as a key component of histopathology education. Recent trends of incorporating visual and interactive technology in active and...
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Bias reduction in representation of histopathology images using deep feature selection
Appearing traces of bias in deep networks is a serious reliability issue which can play a significant role in ethics and generalization related...
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Clustering-based spatial analysis (CluSA) framework through graph neural network for chronic kidney disease prediction using histopathology images
Machine learning applied to digital pathology has been increasingly used to assess kidney function and diagnose the underlying cause of chronic...
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Combinatorial therapy with BAR502 and UDCA resets FXR and GPBAR1 signaling and reverses liver histopathology in a model of NASH
Non-alcoholic steatosis (NAFLD) and steatohepatitis (NASH) are two highly prevalent human disorders for which therapy remains suboptimal. Bile acids...
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A novel dataset and efficient deep learning framework for automated grading of renal cell carcinoma from kidney histopathology images
Trends of kidney cancer cases worldwide are expected to increase persistently and this inspires the modification of the traditional diagnosis system...
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Next-Generation Morphometry for pathomics-data mining in histopathology
Pathology diagnostics relies on the assessment of morphology by trained experts, which remains subjective and qualitative. Here we developed a...
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Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients
Histopathologic assessment is indispensable for diagnosing colorectal cancer (CRC). However, manual evaluation of the diseased tissues under the...
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Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
Timely detection of Barrett’s esophagus, the pre-malignant condition of esophageal adenocarcinoma, can improve patient survival rates. The...
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Histopathology imaging and clinical data including remission status in pediatric inflammatory bowel disease
The incidence of inflammatory bowel disease (IBD) is increasing annually. Children with IBD often suffer significant morbidity due to physical and...
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A comparative multi-level toxicity assessment of carbon-based Gd-free dots and Gd-doped nanohybrids from coffee waste: hematology, biochemistry, histopathology and neurobiology study
Here, a comparative toxicity assessment of precursor carbon dots from coffee waste (cofCDs) obtained using green chemistry principles and Gd-doped...
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Molecular histopathology of matrix proteins through autofluorescence super-resolution microscopy
Extracellular matrix diseases like fibrosis are elusive to diagnose early on, to avoid complete loss of organ function or even cancer progression,...
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Multidisciplinary diagnosis and treatment training simulation by paired teachers using case-based teaching of oral histopathology that promotes clinical thinking
The multidisciplinary diagnosis and treatment (MDT) model has significant advantages in the diagnosing and treatment of intricate cases. In addition,...
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Cluster-based histopathology phenotype representation learning by self-supervised multi-class-token hierarchical ViT
Develo** a clinical AI model necessitates a significant amount of highly curated and carefully annotated dataset by multiple medical experts, which...
