Pathology

Identifying and validating ITGB2 and HNRNPAB as diagnostic biomarkers in chronic obstructive pulmonary disease using bioinformatics and Integrated Machine Learning Methods.

BACKGROUND AND AIM: COPD is a common respiratory disease characterized by progressive airflow restriction that severely affects patients' quality of life and leads to significant mortality rates worldwide. This study aims to strengthen the early diagnosis of COPD and develop personalized treatment strategies. METHODS: The methodology involved a comprehensive approach, including differential gene e...

Optimizing breast core needle biopsy biomarker throughput using an AI-based workflow.

AIMS: To evaluate the feasibility, appropriate relevance and impact on turnaround time (TAT) of an AI-supported workflow in which AI, integrated in the Laboratory Information System (LIS) as well as in the daily workflow, autonomously triggers breast biomarker testing (ER, PR, HER2, Ki-67) for breast core needle biopsies with a high AI-based likelihood of invasive breast cancer. METHODS AND RESULT...

Artificial intelligence in kidney cancer: a review of clinical applications across the disease spectrum.

PURPOSE OF REVIEW: This review examines recent advances (2024-2025) in the application of artificial intelligence (AI) to kidney cancer diagnosis, pro...

LRF-CNN: An explainable lightweight receptive field-based CNN for colorectal cancer histopathological image classification.

Colorectal cancer (CRC) screening and diagnosis rely on histopathological assessment, but many high-performing deep learning (DL) models remain comput...

Prognostic Significance of Baseline 18F-FDG PET/CT Parameters in Combination with an Artificial Intelligence-Based Pleural Effusion Segmentation Model for Malignant Pleural Effusion.

OBJECTIVES: We aimed to use an artificial intelligence (AI)-based pleural effusion segmentation model on baseline 18F-FDG positron emission tomography...

Uncovering G Protein-Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis.

BACKGROUND: Low-grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein-coupled receptors (GPCR) contribute to glioma mal...

A hybrid deep learning framework for accurate breast cancer classification using MRI images.

Early and accurate detection of breast cancer is crucial to enhance patient results, especially in high-risk populations where magnetic resonance imag...

Deep learning based automated detection and grading of oral epithelial dysplasia: A comparative histopathological image analysis.

OBJECTIVE: To develop and comparatively evaluate multiple deep learning architectures for automated detection and grading of oral epithelial dysplasia...

Multi-dimensional analysis revealing the mechanism of T-2 toxin driving liver fibrosis: integration of network toxicology, machine learning, experimental verification, and molecular docking.

BACKGROUND: T-2 toxin is a highly toxic mycotoxin commonly present in food and the environment, with accumulating evidence supporting its hepatotoxic ...

Development and Validation of a Deep Learning-enabled Single Breath-hold Abbreviated MRI Protocol for Hepatocellular Carcinoma Diagnosis.

Purpose To develop a deep learning-enabled single breath-hold abbreviated MRI (DL-SBH-aMRI) protocol for hepatocellular carcinoma (HCC) diagnosis. Mat...

PFAS is associated with perineural invasion in triple-negative breast cancer with a potential role for Cathepsin D dysregulation: a multi-omics and experimental study.

Per- and polyfluoroalkyl substances (PFAS) are persistent pollutants linked to breast cancer (BC), but their role in perineural invasion (PNI) of trip...

Interpretable machine learning models for bladder cancer overall survival prediction development and external validation via SEER database and Chinese cohort analysis.

OBJECTIVE: We developed interpretable machine learning(ML) models to predict overall survival in bladder cancer patients. This approach aims to improv...

Targeting tumor-associated G-protein coupled receptors: beyond single-axis inhibition toward multidimensional regulation.

G protein-coupled receptors (GPCRs) serve as central hubs in tumor signal transduction and microenvironment regulation. However, their therapeutic exp...

Multimodal data integration to determine viral and innate immune kinetics in human airway epithelium.

Understanding the mechanisms that govern viral spread in human airway epithelium (HAE) remains a major challenge, particularly with regard to identify...

Artificial intelligence in the care of systemic lupus erythematosus: Current capabilities and translational barriers.

BackgroundThe clinical heterogeneity of systemic lupus erythematosus exceeds the resolution of conventional disease activity instruments. Artificial i...

Cellular and subcellular heterogeneity of astrocytic Na⁺ homeostasis tuning astrocytes into functionally distinct subgroups in the mouse brain.

Astrocytes maintain extracellular ion and transmitter homeostasis, with the Na⁺ inward gradient playing a crucial role. Earlier studies suggested a ra...

Intelligent Manufacturing: A Fully Annotated Synthetic Dataset for Fiber Orientation Estimation.

This work introduces a fully annotated synthetic dataset designed to support machine learning-based estimation of fiber orientation in short-fiber rei...

A temporal keyword co-occurrence network mining framework for detecting structural transitions in cancer biomarker research (2006-2023).

Biomarker research for cancer diagnosis and prognosis has rapidly expanded technologically and thematically, along with advancements in molecular diag...

Integrating multi-omics data for next-generation cancer research and precision medicine.

Multi-omics is the coordinated acquisition, integration, and interpretation of multiple datasets generated from diverse molecular layers of a biologic...

Pulmonary nodule growth prediction with anisotropic reaction-diffusion.

BACKGROUND AND OBJECTIVE: Accurate prediction of pulmonary nodule growth is critical for early malignancy assessment and timely lung cancer diagnosis....