Pathology

Automated 4D flow MRI pipeline for the quantification of advanced hemodynamic parameters in the left atrium.

The left atrium (LA) plays a pivotal role in modulating left ventricular filling, yet its hemodynamics remain poorly understood due to the limitations of conventional ultrasound analysis. Four-dimensional flow magnetic resonance imaging (4D Flow MRI) holds promise for enhancing our understanding of atrial hemodynamics, but its analysis is hindered by the inherently low velocities within the chambe...

Robust and interpretable prediction of gene markers and cell types from spatial transcriptomics data.

Spatial transcriptomics (ST) links tissue morphology with gene expression values, opening new avenues for digital pathology. Deep learning models are used to predict gene expression or classify cell types directly from images, offering significant clinical potential but still requiring improvements in interpretability and robustness. We present STimage as a comprehensive suite of models to predict...

Towards interpretable prediction of recurrence risk in breast cancer using pathology foundation models.

Transcriptomic assays such as the PAM50-based ROR-P score guide recurrence risk stratification in non-metastatic, ER-positive, HER2-negative breast ca...

A machine learning-driven Raman spectroscopy approach for non-invasive diagnosis of non-puerperal mastitis.

Early and rapid diagnosis of non-puerperal mastitis (NPM), as well as elucidation of its specific pathological features, is of important clinical and ...

Synovial transcriptome analysis reveals ShenTong ZhuYu Tang alleviates osteoarthritis by targeting MMP-9 and immune microenvironment.

BACKGROUND: This study aimed to elucidate key molecular alterations in the osteoarthritis (OA) synovial microenvironment through transcriptomic analys...

Impact of a new deep-learning image reconstruction algorithm on potential dose reduction and quality of chest CT images: a phantom study.

PURPOSE: To evaluate the impact of a new deep-learning image reconstruction (DLR) algorithm on image quality and potential dose reduction compared wit...

LGDUnet: A dual-branch network for weakly supervised gland segmentation in H&E stained histopathological images.

Glandular segmentation holds significant importance in the pathological analysis of hematoxylin and eosin (H&E) stained images, particularly in the di...

Small-molecule fluorescent probes for the aminergic GPCRs - What new tool compounds do we have post-2014 and what can they do?

Aminergic G protein-coupled receptors (GPCRs) are heavily involved in the physiological functions of the human body and represent prominent drug targe...

Diagnostic Accuracy of the National Library of Medicine (NLM) Screener Application in Screening for Malaria Parasites Among Blood Donors at the Korle-Bu Blood Bank, Ghana: A Cross-Sectional Study.

BACKGROUND AND AIMS: Malaria is a deadly disease spread through the bite of an infected female Anopheles mosquito and remains the leading cause of mor...

MAGED: Multimodal attentive graph learning with gene expression dynamics on knowledge graphs for TCM target prediction.

ETHNOPHARMACOLOGICAL RELEVANCE: Plants used in traditional medicine have long provided valuable clues for drug discovery, yet systematically connectin...

Artificial Intelligence in Pleural Diseases: Current Applications and Next Steps.

Pleural diseases pose a significant burden on healthcare systems due to diagnostic challenges and high costs. Artificial intelligence (AI) has the pot...

Imaging and Quantification of Perivascular Adipose Tissue.

Perivascular adipose tissue (PVAT) is a metabolically active tissue that influences vascular function through paracrine signaling of adipokines. Patho...

From observation to understanding: A multi-agent framework for smart microscopy.

Smart microscopy represents a paradigm shift in biological imaging, moving from passive observation tools to active collaborators in scientific inquir...

Biologically explicable multimodal model predicting local tumor progression and tumor invasiveness of hepatocellular carcinoma.

PURPOSE: Local tumor progression (LTP) of hepatocellular carcinoma (HCC) after thermal ablation (TA) is related to tumor invasiveness and threaten the...

DPM: A Deep Learning and Optimal Transport Framework for Cost-Effective Spatial Metabolomics.

Mass spectrometry imaging (MSI) is a powerful technology in spatial metabolomics that enables the in situ detection and distribution analysis of metab...

Segmentation and calculation of lung fibrosis in IPF mice by 2.5D UNet.

BACKGROUND: Idiopathic pulmonary fibrosis significantly threatens patient survival and remains a condition with limited effective treatment options. T...

[Extracellular matrix materials and tissue regeneration and repair].

The extracellular matrix (ECM) plays a pivotal role in regulating cellular behavior and driving tissue regeneration. Its unique structural characteris...

Modeling Ischemic Stroke Pathological Dynamics via Continuous Fields and Vector Flow.

Precise localization of perfusion deficits in diffusion-weighted MRI (DWI) is critical for acute ischemic stroke management. However, existing deep le...

Investigating the molecular mechanisms of glutamine metabolism and mitochondria-related biomarkers in Alzheimer's disease through transcriptomics and experimental validation.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder. This study aims to identify biomarkers associated with glutamine metab...

[Study of the performances of conversational agents in interpreting textual description of lesions in pathology].

The applications of artificial intelligence (AI) in anatomical and cytological pathology (ACP) are growing, particularly in image analysis. Conversati...